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In 2024 alone, the medical imaging software market size reached $8.11B. By 2029, it is projected to grow to $11.83B and up to 7.84% at a CAGR. This is a fairly predictable trend due to the development of AI. Especially since big data, cloud technologies, and other advancements are already significantly speeding up the accuracy of diagnostics.
If you are considering custom development of medical image analysis software, now is the most favorable time. Below, we will reveal the specifics of creating such solutions and describe the requirements and the challenges you may face.
What is the definition of medical imaging software?
Medical imaging software — it's the digital tool doctors use to examine medical images. Think X-rays, MRI and CT scans, ultrasounds, PET, and other radiology scans. Basically, it helps to see the details of every complex illness and make informed decisions about patient care.

To maximize efficiency, medical imaging software integrates a range of advanced technologies. These include AI for anomaly detection, ML for image segmentation, and methods for filtering, contrast enhancement, and noise reduction to improve image quality.
Also, 3D reconstruction technologies create volumetric models of organs and tissues. Developers also rely on the DICOM standard for medical images as it allows seamless transfer. They also use cloud tech to access data, integrated medical records, and VR and AR to visualize data and create interactive interfaces.
As a result, with medical image analysis software, healthcare organizations reduce the workload of their doctors and researchers and minimize the likelihood of misdiagnosis.
Examples of medical imaging software
To better grasp how these solutions work, we suggest you look at several medical imaging software examples that have gained worldwide recognition.
RadiAnt DICOM viewer
It is a high-performance medical imaging software that processes DICOM images. Due to its rich functionality, both doctors and researchers use it in their work. It has smart multimodality tools for 3D and 2D visualization and MPR (multiplanar reconstruction). Moreover, developers made the interface very user-friendly, so this software is also a great choice for users with low technical skills.

OsiriX MD
Specifically designed for macOS, OsiriX MD is a powerful DICOM platform that meets the needs of radiologists. Its advanced capabilities support 3D and 4D image analysis, hybrid imaging with PET-CT and PET-MRI, and integration with PACS servers. Crucially, it is FDA- and CE-certified for clinical use.

Horos
Horos is a free OsiriX-based DICOM viewer available on macOS. It has rich customization options for analyzing volumetric data, such as 3D reconstruction, and is especially useful for students and researchers.
GE Healthcare Centricity PACS
GE Healthcare Centricity PACS is a proprietary enterprise medical image analysis software that analyzes medical images. It has EHR and EMR integration, real-time collaboration, advanced AI analysis, DICOM standards, and format support. It can be a full-fledged assistant for doctors and researchers.

Philips IntelliSpace Portal
Tailored for large clinical institutions, Philips IntelliSpace Portal excels in medical image analysis and visualization. It integrates AI-driven automation and tools for multiparametric imaging in cardiology, neurology, and oncology; this medical imaging software supports multi-user collaboration.
Key features of medical image processing software
This section explores the key functionalities typically found in standard medical imaging software.
Tools for viewing and processing medical images
Ensure your medical imaging software works with various input data (CT scans, MRI scans, X-rays, ultrasounds, and hybrid studies like PET-CT and PET-MRI). Usually, this is done by supporting the DICOM format. In addition, you will need tools to scale, rotate, and adjust image contrast. So, optionally, develop a panel for 3D and 4D visualization, including multiplanar reconstruction.
AI-driven image analysis
AI is key in automating the detection of anomalies in medical scans. It can identify cancerous tumors, blood clots, and fractures early, with a high degree of independence. Also, AI in your medical imaging software can classify pathologies using trained models. It can segment organs and tissues on scans and analyze multiparametric data.
Diagnostic and treatment planning tools
This includes tools for creating 3D models, surgical planning, and evaluating the effectiveness of treatment. You should also consider integrating your medical imaging software with robotic surgical systems.
Medical data management tools
To implement effective medical data management, you will probably need to integrate your medical imaging software with PACS (for storing and transmitting data), EHRs (for centralized access to personal patient information), and cloud solutions (for unimpeded access to images from anywhere in the world where there is an Internet connection).
Collaboration tools
It's mainly for remote access so doctors and specialists can chat and comment on each other's actions. It also involves integrating telemedicine platforms to discuss complex cases and hold educational seminars.
What types of organizations need medical image analysis software development?
A wide range of organizations can benefit from medical image analysis software development. Now, let's find out which areas of healthcare benefit from medical imaging software the most.
- Cardiology.
In this field, medical imaging software is mostly used to analyze CT and MRI of the heart and angiography. In addition, it monitors treatment effectiveness, plans operations, and predicts cardiovascular disease risks.
- Dentistry.
Inevitable for 3D scanning when planning dental implants, diagnosing jaw diseases, visualizing root canals, etc.
- Oncology.
Here, medical imaging software detects and classifies tumors, tracks their growth, and assesses treatment effectiveness.
- Neurology.
In this sector, medical image analysis software analyzes brain MRIs and CTs and provides 3D visualizations to assess the spine and nerves.
- Orthopedics.
Orthopedics studies thrive on precise X-ray analysis, which includes 3D joint modeling and spinal disease diagnostics.
- Mammology.
Medical imaging software can detect microcalcifications and early breast cancer through comparative analysis of changes in mammary gland tissue.
- Urology.
In this industry, medical imaging software helps diagnose kidney and bladder diseases. It does this by analyzing CT and ultrasound images. Additionally, the software can help plan operations and monitor patients with chronic diseases.
- Pulmonology.
Industry specialists can use such software to diagnose lung diseases, analyze chest CT data, and assess COVID-19 damage.
- Gynecology.
In most cases, medical image analysis software is used to perform pregnancy ultrasounds. It helps monitor the fetus, find pelvic tumors, and analyze the endometrium and other tissues.
- Traumatology and emergency medicine.
In traumatology, 3D medical imaging software can quickly diagnose fractures and internal injuries. It can also visualize organs for urgent decisions.

Still, deciding on the right healthcare sector for your medical imaging project? Contact us and discuss the possibilities of its practical implementation with Darly Solutions' experienced developers.
Medical imaging software development: Steps to follow
Custom development must follow clearly defined stages that most teams use. But, it can still be approached in various ways. Below, we outline how healthcare software development services are delivered in our company.
Concept formation
Start your medical imaging software project with market analysis. Define the target audience, prioritize tasks the software should solve, and research competitors (to identify their strengths and weaknesses). Based on the insights, our medical imaging software development team assesses the functional requirements and evaluates the need for specific technologies to handle image processing. This ensures that the chosen solutions align with the project's technical needs and optimize the processing of healthcare-related images.
Planning
Once we agree on the conditions with all stakeholders, we will write a technical specification for your medical imaging software. This document will describe its functionality, interface, API, security, and integration requirements. We will also approve the tech stack and necessary integrations. Finally, we create a roadmap that defines the milestones and deliverables for each medical imaging software development project stage.
Prototyping
Now that everything is ready, we can begin creating user stories. They include handling DICOM file uploads and 3D models, among other key tasks. For UX/UI best practices of safe data, we follow the WCAG 2.1 guidelines. They ensure accessibility for users with varying technical skills. We also test prototypes with focus groups to see feedback on complex features, which is helpful for future design improvement. Finally, after the edits are done, we develop a full-fledged design.
Coding
The frontend has algorithms to process and analyze medical images. The backend ensures secure data transfer between the medical imaging software and storage. It also encrypts data and protects against vulnerabilities like SQL injections. These involve writing database queries for smooth software interactions and data storage interactions. And last but not least — we also integrate with your healthcare org's existing systems and services (if any).
Testing
Once the code for your medical imaging software is ready and all components have passed unit tests, we run complete test cases. We check for load, functional, non-functional, security, and usability issues.

Deployment
At this stage, we are choosing hosting for your medical imaging software (usually either cloud or local servers), setting up CI/CD, and training end users, for example, by providing them with documentation, training materials, or live courses. Once we've done it, we deploy the solution (first in the test environment and then — in the actual usage environment).
Support and updates
Finally, after the medical imaging software is deployed, we set up monitoring systems to track its performance and detect errors, fix post-release bugs, optimize it according to user feedback, and add new features if required.
Key tech specifications for medical imaging software development
Such software development can be complex, especially in its early stages. Basically, there is often no clear way to turn an abstract idea into actual requirements.
So, let's examine all the key tech specifications that are usually implemented in medical imaging software apps:
- Support for common medical image formats such as DICOM (including DICOM tags for metadata) and standards for storing, transmitting, and processing medical images (such as C-STORE, C-FIND, and C-MOVE).
- Compatibility with various devices (CT, MRI, ultrasound, etc.).
- Image processing can improve images by adjusting contrast brightness and applying filters. It can also segment them to highlight organs and tissues. Lastly, it can register them to compare scans over time.
- 2D and 3D visualization, including volume rendering (CT/MRI), support for iso-sections and reconstructions, and interactivity (e.g., rotation, zoom, and pan).
- Data security, including HIPAA and GDPR compliance, support for TLS (for data transfer) and AES-256 (for image and metadata storage) encryption standards, as well as access control with role-based authorization and two-factor authentication.
- PACS and EHR/EMR integration (e.g., via HL7/FHIR).
- Annotation (adding labels, arrows, and text comments) and providing real-time collaboration tools.
- PDF report generation and image export.
- Scalability (including horizontal scaling via the cloud), multi-threading, and hardware acceleration.
- WCAG 2.1 compliance and user interface customization.
- Logging and monitoring events (including loading, processing, and exporting scans), auditing user access, tracking system performance, and setting up failure notifications.
- Local deployment of software on physical servers (most likely, this will require ensuring compatibility with Linux and Windows OS).
- Setting up regular data backups and automatic recovery after system failures.
Of course, this is just a basic list of specifications. In practice, your project team will expand and refine the list of features while specifying the tools and technologies for the project's unique needs.
Medical imaging software development cost
When it comes to the development cost of medical image analysis software it depends on its complexity and the technologies used. Without data and business needs — it's hard to define the precise price, but on average, basic DICOM (Digital Imaging and Communications in Medicine) typically ranges from $30K to $300K. A customized version of Basic DICOM may cost $30K to $50K. Advanced customizations could cost $70K to $150K.
Implementation costs differ based on the size of the practice:
- Small practices typically cost $5K to $10K and take 1 to 2 weeks.
- Medium facilities cost $20K to $50K and take 1 to 3 months.
- Large enterprises may cost $100K to $200K and take 3 to 6 months.
Please complete this form to calculate the precise budget for your medical imaging software development idea. We will contact you shortly.
Challenges in medical imaging software development
Let's examine the main challenges encountered when developing medical imaging software.
- Regulatory compliance.
Software handling sensitive data, like patient information, must comply with HIPAA, GDPR, FDA 21 CFR Part 11, and CE Marking regulations. Key security measures include code audits, RBAC, 2FA, and strong encryption (e.g., AES-256, TLS).
To avoid fines, consult a local lawyer on medical standards.
- Integration with existing systems.
Integrating PACS, EHRs, and other systems requires DICOM, HL7, and FHIR support. Also, medical organizations have very different established IT infrastructures, which makes it hard to unify their software. If you create a universal solution, you must provide some middleware. It will help users adapt to various services and systems.
- High performance and scalability.
Medical images, especially CT and MRI, are large. This can slow their processing and increase resource needs.
In this regard, you may need to implement lossless compression mechanisms for images and multithreading and parallel data processing algorithms. By the way, a common fix is to move your software to a cloud solution designed for healthcare businesses.
- The complexity of big data management.
Storing and processing massive data, like images and metadata, require a careful choice of databases and storage. In particular, this implies a preference for distributed databases and object storage.
For even greater reliability, do not forget to provide backup and auto-recovery.
- Risks associated with cyber attacks.
Cyber attacks that leak medical data are a serious problem for healthcare software. To solve it, you must implement constant monitoring. Also, set up regular security updates, including patches and OS updates.
Finally, train your staff on social engineering. It can reduce the risks of phishing attacks.
Providing a user-friendly interface.
Interfaces for doctors and medical personnel should be user-friendly and intuitive, requiring minimal technical training to operate efficiently. To achieve this goal, you must test hi-fi prototypes on the real target audience and perform subsequent optimizations. Also, do not forget to ensure your interface is created under the WCAG 2.1 guidelines.
The future of medical imaging software
Medical imaging software development will advance by adopting the newest technologies, process optimization, and increased integration with other medical systems.
So, here are the core areas in which medical imaging software can be optimized:
- Speeding up diagnostic.
- Increasing image recognition accuracy.
- Costs reduction.
- Improving user experience.
This can be achieved through the implementation and development of the following technologies:
- Artificial intelligence and machine learning.
For highly accurate and automatic analysis of medical images and accelerated diagnostics.
- Cloud computing.
To provide quick access to medical images from anywhere in the world, process large amounts of data without the need to upgrade local infrastructure, and implement remote collaboration between healthcare specialists.
- VR/AR.
Medical imaging software development allows anatomy and pathologies to be studied using interactive 3D models and visualize the patient's anatomy before surgery.
- Quantum computing.
While most quantum computers are not yet available for widespread use, they will speed up processing large datasets and training neural networks for image recognition in a few years.
- Blockchain.
To guarantee the immutability and protection of data from medical imaging software while providing patients with comprehensive control over their medical information.
Our experience in medical imaging software development
This section covers the development of the PrismaORM brain scanner. This platform was crafted for chiropractors, neurologists, and neurosurgeons to monitor brain activity and brainwaves before, during, and after chiropractic treatments.
First, we assembled a team of eight experts to bring this vision to life. They worked closely with two external teams of medical imaging software engineers. We've pointed out a tech stack based on PostgreSQL, Typescript, React Native, Nest.js, Expo, Three.js, and SQLite. This tech of choice lets us build a platform that processes real-time data from brain activity helmets. The BLE protocol transmits this data. A tablet interface visualizes it. A key to the project's success was optimizing the user experience. This included better platform performance and integrating 3D models.

As a result — we've made a powerful tool that empowers medical professionals to conduct more precise diagnostics and offer more effective treatment recommendations.
For a detailed look at this project, visit our portfolio.
Wrapping up
Now that you understand the specifics of medical image analysis software development, you can begin searching for a team to bring your project to life. We are a reliable provider of custom healthtech solutions, ensuring a smooth, transparent, and predictable collaboration. Simply fill out the form, and we'll get in touch as soon as possible to discuss your medical imaging software project in detail.

The implementation of artificial intelligence (AI) and machine learning (ML) has the potential to turn the healthcare industry upside down. And this global transformation is already beginning. Innovative technologies are being used in diagnostics and treatment. They are influencing pharmaceuticals, research work, and other aspects of medical practice.
Analysts at Global Market Insights have calculated that the AI market in healthcare is valued at $18.7 billion. However, by 2032, the situation will change. According to forecasts, its size will exceed $317 billion.

Considering this trend, we find it appropriate to explore the prospects that AI and the technologies based on it offer to medical professionals worldwide. We will also focus on the near future of AI-based medical solutions and discuss examples of digital products that are already available to specialists.
What Are Machine Learning Healthcare Projects?
Machine learning projects in the medical field involve the use of ML algorithms and models to perform various tasks for healthcare workers. These include:
- data collection and analysis;
- predicting the condition of patients and treatment outcomes;
- making decisions about the appropriateness of certain prescriptions, and more.
The effectiveness of using AI and ML in healthcare is confirmed by numerous specialized studies. Below are some examples:
- The Houston Method Research Institute used an AI-based tool for diagnostic purposes. Specifically, it was used to detect malignant breast tumors. The results shocked scientists. The system demonstrated a disease detection accuracy approaching 99%. Moreover, AI was able to analyze mammograms 30 times faster than humans.
- The Nationwide Korean Cohort Study focused on researching the effectiveness of predicting infectious disease outcomes using machine learning. The results showed that the accuracy of the applied ML model was over 90%.
- Scientists from Indiana University and Purdue University in Indianapolis developed an ML-powered system to predict the outcome of acute myeloid leukemia. The results of the model's tests demonstrated that it could predict remission with 100% accuracy. The likelihood of recurrence was correctly identified in 90% of cases.
- Researchers at BMJ Health & Care Informatics developed and tested a machine learning model for detecting NASH (non-alcoholic steatohepatitis). This disease is difficult to diagnose. However, the use of ML contributes to more accurate screening of NASH and allows for the timely application of effective treatments.
All of these statistics confirm the vast potential of machine learning in healthcare projects. So, what is this technology most often used for?
Popular Use Cases of AI Projects in Healthcare
According to Morgan Stanley Research, 94% of respondents (medical companies) reported using AI or ML in their practice.

Let’s take a look at which aspects of healthcare these technologies can optimize.
1. Pathology Detection
Machine learning models can be used to analyze various types of images. The goal is to recognize pathological conditions.
For example, they can be used to diagnose cancer, tuberculosis, and other infections.
How does this work in practice? Here are several examples of using ML in the field of pathology detection:
- A machine learning-based program analyzes tissue samples and helps identify malignant growths.
- ML algorithms recognize tuberculosis by examining sputum samples from an infected person.
- ML-based systems help differentiate between benign and malignant tumors.
An example of such software is AIM-PD-L1: an AI and ML-based tool that detects PD-L1. This protein is formed as a result of cancer cell development. Research on this solution showed that its results closely align with human diagnostics. Thus, the tool can be useful in identifying pathology.
Another solution from the same developer, PathAI, is the PathExplore panel for histopathological features. It can analyze tissue images at the pixel level. This allows it to examine millions of cells and accurately identify malignant ones.
2. Medical Imaging and Diagnostics
Healthcare machine-learning projects often use innovative technologies to analyze various images. These include CT scans, MRIs, mammograms, X-rays, and more.
Here’s how machine learning models can be used in diagnostics based on visual data:
- An ML-based system can analyze CT scan results and, with a high degree of accuracy, identify malignant tumors.
- Similarly, such platforms can diagnose ischemic strokes, such as hemorrhage, based on brain MRIs.
- Specialized ML-based tools allow for retina scans. This helps in the early detection of blindness due to diabetes, specifically diabetic retinopathy.
There are many similar solutions available on the market. Among them are Viz.ai and InnerEye.
The first, Viz.ai, is a care coordination system based on AI. It allows for automate detection of many diseases, including vascular pathologies.
The second, InnerEye, is a solution from Microsoft that significantly speeds up work with patient images. For example, with this platform, doctors can accurately differentiate between healthy and cancerous cells. It also accelerates the start of treatment by 13 times.
3. Personalized Medicine
Each patient is unique due to the following characteristics:
- genetic predisposition;
- medical history;
- lifestyle;
- comorbid health issues, and more.
Machine learning-based platforms are able to take all these factors into account when selecting treatment methods.
Here’s how this can work in practice:
- ML models analyze genomic data and recommend individualized treatment methods for oncological diseases.
- Thanks to predictive analytics, AI-based tools can adjust insulin dosage. This is possible through constant monitoring of its level in the patient.
- Machine learning algorithms help choose the optimal antidepressant based on the patient's psychological state and genetic predispositions.
As an example, let's look at IBM Watson for Oncology. This is a machine learning-based system that considers many factors when recommending cancer treatments. These include the compatibility of prescribed medications, possible side effects, and the effectiveness of treatment in each specific case. As a result, the system provides healthcare professionals with several therapy options from which they can choose the most optimal.
4. Drug Discovery Process
The use of ML can accelerate the invention of new pharmaceuticals. Specialized systems show excellent results in discovering the medicinal properties of various substances. They can also analyze the interactions of drug components and optimize clinical trials.
AI in healthcare projects can be used for this purpose as follows:
- ML models accelerate the search for antibiotics and antiviral drugs.
- AI-based modeling helps reduce the number of failed clinical trials, thus saving time and resources.
- Machine learning algorithms can analyze the structure of substances, assisting in the development of new drugs.
A notable example of using AI and ML in creating new drugs is AlphaFold by DeepMind. This tool is designed to determine the structure of proteins, which are the foundation of biological processes in every living organism. Currently, the platform is successfully used for:
- fighting malaria;
- searching for a treatment for Parkinson's disease;
- counteracting bacteria resistant to existing drugs.
5. Epidemic Prediction
One of the capabilities of ML models is analyzing patterns and making predictions about outbreaks of various diseases.
Here are some examples of using ML-powered solutions:
- Such systems can predict global pandemics. To do this, they analyze data on population movement and disease statistics.
- ML algorithms track seasonal disease spikes, such as the flu.
- “Smart” platforms can predict outbreaks of specific diseases in high-risk areas. For example, they can forecast cases of malaria or dengue fever.
EPIWATCH is one of the leading examples of such platforms. This tool uses artificial intelligence to predict epidemics that could reach a global scale. The system collects and processes extensive infectious disease data in real time. It has proven effective in providing early warnings about potential pandemics.
6. Remote Patient Monitoring
In recent years, IoT (Internet of Things) devices have become widely used in medicine. These are objects equipped with sensors that can collect and transmit data wirelessly without human intervention.
According to Yahoo!Finance, the IoT market in healthcare, was valued at $58.8 billion in 2024, and by 2032, it is expected to exceed $305.5 billion.

This situation is explained by the fact that AI and ML enhance the efficiency of wearable devices and health monitoring systems in general.
The use of ML in remote monitoring includes the following cases:
- Smartwatches can track irregular heart rhythms and detect instances of sleep apnea.
- ML models can analyze ECG data in real time. Based on the obtained data, they can predict a heart attack.
- AI-based inhalers can track the patient’s readings and warn about an asthma attack.
There are many such solutions on the market. These include popular devices like the Apple Watch and Fitbit. These smart bracelets can monitor heart rhythms and detect uncontrolled breathing stops.
There are also more complex systems available to healthcare professionals. For example, SafeBeing from Somatix. Thanks to wearable devices, this platform responds to patient gestures and draws conclusions about their health condition.
7. Virtual Assistants
Not everyone can visit a medical facility in a timely manner. Moreover, many people need assistance and support after being discharged from the hospital. AI handles these challenges effectively. Developers are actively creating digital assistants with integrated ML algorithms. These assistants are capable of providing first-aid and consulting patients after treatment.
What can such tools do?
- These platforms help assess health status independently and suggest possible diseases.
- Smart chatbots help schedule doctor visits, remind patients to take medications, and more.
- Virtual assistants help monitor the progress of chronic diseases.
There are many such solutions available to patients. Let’s look at the features of Ada Health as an example. This platform helps assess symptoms and provide preliminary diagnoses using machine learning algorithms. It can:
- track changes in the body over time;
- provide recommendations regarding treatment and a healthy lifestyle.
8. Psychiatric Assistance
ML algorithms help diagnose and treat various psychiatric disorders, including those used in the fight against depression and anxiety.
Practical examples of ML usage in psychiatry:
- Intelligent chatbots can mimic real-world conversations. They can answer patients' questions and provide recommendations.
- ML models can analyze user behavior on social media and detect suicidal tendencies.
- These digital solutions can analyze human speech and identify early signs of Alzheimer’s disease.
Woebot is a smart chatbot that helps people with mental health disorders. It can assess a user’s mood and emotions. Among its functions are conducting conversations with patients and providing personalized strategies for coping with difficulties.
9. Robotic Surgery
Just imagine. Surgeons no longer need to be in the operating room. All procedures are performed by a robot. Sounds like a scene from a sci-fi movie? Nevertheless, this is our reality. Developers have already created robotic systems based on AI that enhance the accuracy of surgical interventions and reduce rehabilitation time.
What can such software do?
- Smart surgical systems can perform minimally invasive surgeries.
- AI-based software shows excellent results in neurosurgery and orthopedics.
- ML models predict potential surgical risks and possible complications.
Here, we cannot fail to mention the famous Da Vinci surgical robot created by Intuitive Surgical. This robotic system offers medical professionals incredible possibilities in the field of minimally invasive surgery. Its features include fluorescence visualization, integrated table movement, a vision cart, and more. This allows for precise and effective surgical interventions.
10. Automation of Administrative Tasks
Routine tasks such as organizing document flow or billing require a lot of time, diverting medical staff from their primary duties — treating patients. The implementation of machine learning-based software allows automation of these processes, reducing the time spent by medical personnel.
AI-powered systems are handling numerous administrative tasks:
- Platforms based on NLP can extract data from medical records and update patient electronic charts.
- ML algorithms analyze insurance cases, minimizing fraudulent claims.
- Smart scheduling systems efficiently manage hospital resources.
An example of such software is the Optum system. It offers numerous solutions for the healthcare business, including a platform for Revenue Cycle Management. Its capabilities include billing, increasing revenue efficiency, medical coding, and documentation.
Benefits of Machine Learning for Healthcare Analytics Projects
The use of ML models in healthcare allows for the analysis of large amounts of medical data. Furthermore, such models are continuously trained and improved. The implementation of tools based on these models brings a number of benefits to both medical professionals and patients:

Early Disease Diagnosis
Identifying serious diseases at early stages reduces mortality, improves the quality of life for patients, and increases the likelihood of full recovery or sustained remission. For medical institutions, this helps reduce their expenses and saves time.
ML models excel at early diagnosis. They analyze medical images, test results, and patient medical histories. They then track patterns and detect even the slightest deviations from the norm.
Improvement in Patient Care Quality
This is facilitated by AI-based digital solutions for personalized care, virtual assistants, and chatbots. They help maintain a person's health outside of the hospital, for instance, after discharge or before visiting a specialist.
At the same time, such platforms help reduce the workload on medical institutions. They can provide the patient with an initial consultation and allow medical professionals to remotely monitor the patient's condition.
Development of the Pharmaceutical Industry
Innovative technologies allow for faster development of new medications. This is a step toward effectively combating various diseases. This is particularly relevant during global epidemics.
Cost Reduction
ML automates many processes in healthcare, from documentation management in clinics to diagnostics and treatment prescriptions. Additionally, the use of smart technologies helps reduce human errors and allows for some patients to switch to home care. As a result, medical institutions can increase the number of patients served and their profits.
Improvement in Treatment Effectiveness
In medicine, predictive models are used, which are trained on large sets of historical patient data. Such models can predict:
- the likelihood of recurrence;
- the need for hospitalization;
- the tendency for the disease to progress.
Medical professionals can use all this data to adjust the prescribed treatment to improve its effectiveness.
Key Challenges in Healthcare Machine Learning Projects
The implementation of machine learning in healthcare projects opens up many opportunities for the industry. We have already seen this today. However, alongside numerous advantages, some challenges may arise for innovators.
Security of Confidential Data
The digitalization of healthcare has led to a particularly sharp issue. We mean the preservation of medical confidentiality and the privacy of patient data. The use of virtual tools implies entering personal information into the system, which increases the risk of data leakage.
To mitigate these risks, maximum anonymity should be maintained. For example, financial and insurance data, as well as the patient's address, should not be included. It is also important to implement reliable data encryption methods and threat notification mechanisms on the platforms.
Quality of Data for Model Training
The effectiveness of ML models depends on the data input into the system. Inaccurate input data can lead to incorrect diagnoses, wrong treatments, and even death.
To prevent this problem, machine learning software should be used under the supervision of highly qualified medical staff.
Skepticism of Healthcare Professionals and Patients
Since machine learning projects in the medical field are still in the early stages of gaining ground, many doctors and patients are not fully confident in its capabilities. The main concerns include inaccurate diagnostics and the complete replacement of human involvement in medical practice.
To build trust, continuous training for healthcare professionals and patients is necessary. It is also important to notify people about the chosen treatment methods.
As for the complete replacement of human labor, this is highly questionable. Scientists believe that innovative technology will, in fact, expand the role of healthcare professionals. Their duties will include overseeing the operation of ML models and interpreting their results.
Difficulty of Integration with Existing Software
To ensure the smooth operation of medical institutions, new software products need to be seamlessly integrated into the existing infrastructure. The task becomes more complex because clinics may be using outdated systems that are not compatible with new technologies.
To solve this problem, investment in qualified IT personnel and gradual replacement of old software with new ones is necessary.
Technologies Used in Machine Learning Projects in Healthcare
Such high efficiency in AI projects in healthcare is achieved thanks to the wide range of technologies used in specialized software. Let's look at the main ones.
Computer Vision
This is the ability of a machine to understand and interpret visual information from the external world. In healthcare, it is used for analyzing medical images for subsequent diagnosis and treatment.
Examples of use:
- detection of tumors in X-rays, CT scans, or MRIs;
- analysis of biopsy results to identify malignant formations.
Robotic Process Automation (RPA)
This involves using bots (software robots) to perform repetitive tasks. In medicine, this technology is applied to automate administrative processes.
Examples of use:
- processing insurance claims;
- billing;
- inputting data into electronic patient records.
Logistic Regression
This is a statistical machine learning algorithm that is effective for predicting the probability of disease and classifying ailments.
Examples of use:
- assessing the risk of developing diabetes;
- determining the likelihood of cardiovascular diseases.
Support Vector Machines (SVM)
This is a supervised machine learning algorithm that is best suited for classification, i.e., separating data into different categories. It is used in medicine for diagnostic purposes.
Examples of use:
- differentiating between benign and malignant tumor cells based on biopsy data;
- classifying genes to identify genetic disorders.
Natural Language Processing (NLP)
This is a field of artificial intelligence that enables computers to understand, interpret, and generate human language. It is used to process medical text, such as doctor’s notes or specialized literature.
Examples of use:
- analyzing electronic medical records to extract patient data;
- virtual assistants and chatbots to assist patients outside medical facilities.
Large Language Models (LLM)
These are a specific type of machine learning models trained on large datasets. Their capabilities include understanding and generating human-like language.
Examples of use:
- answering complex medical questions;
- automating clinical documentation.
Deep Learning (DL)
A subset of machine learning that uses neural networks with multiple layers to perform tasks. It is applicable for image recognition and speech processing. It is widely used in medical imaging, as well as in fields such as genomics and pharmaceuticals.
Examples of use:
- developing new medications;
- diagnosing diseases based on visual data.
Reinforcement Learning (RL)
A type of machine learning where an agent learns by interacting with its environment, in other words, through trial and error. This technology helps optimize the effectiveness of treatment strategies.
Examples of use:
- robotic surgical systems;
- personalized treatment for various diseases.
The powerful potential of AI-based technologies suggests that the future of healthcare lies in them.
Future Trends in AI and Machine Learning in Healthcare Projects
It is predicted that in the coming years, AI and machine learning will continue to strengthen their position in healthcare. This is facilitated by:
- better awareness of these technologies among doctors and patients;
- an increase in the number of developers capable of creating and integrating innovative systems;
- a growing demand for skilled healthcare services and medications.
What can we expect in the near future?

Transformation of Primary Healthcare
AI and machine learning systems will take on more responsibility during a patient's initial visit to the doctor. They will classify patients based on their risk level, using examination results. Patients with a low probability of illness will be notified immediately. Those with a high risk will be referred to specialists.
This will reduce the waiting time for referrals and ease the burden on specialists.
Improvement of Healthcare Accessibility
According to the International Labour Organization, 56% of people living in rural areas have no access to healthcare. In cities, the situation is better but still concerning, with 22% of the population unable to access medical services.
AI and machine learning have the potential to fundamentally change this situation. This will be possible through telemedicine and mobile health services.
Focus on Data Security
AI system developers understand the importance of ensuring data security in healthcare. The HIPAA Journal states that in 2023, over 133 million medical records were exposed due to data breaches. This means the problem is becoming global in scale.
As a result, IT specialists will work on enhancing the reliability of the security measures being implemented.
Progress in Early Disease Detection
Modern intelligent software is capable of recognizing symptoms at the very early stages of disease development. However, in the near future, AI capabilities will go even further. The first steps in this direction are already being taken. An example is the Sybil tool developed by scientists from the Massachusetts Institute of Technology. It can predict the development of lung cancer within a year with 94% accuracy.
This is a huge breakthrough in healthcare. It has the potential to save millions of lives.
Emphasis on Personalized Treatment Plans
Doctors will increasingly move away from general prescriptions that do not account for the specific characteristics of individual patients. AI systems will be used to analyze medical histories, genetics, and other factors. Based on this analysis, personalized treatment methods will be selected.
This approach is particularly relevant for treating complex diseases such as cancer.
Darly Solutions Case Studies
Finally, we would like to share the experience of the Darly Solutions team. Our custom healthcare software development company has implemented many successful AI-powered projects for healthcare.
A company approached us with concerns about patient safety during the diagnosis of infectious diseases. They decided to rely on AI and machine learning for the accuracy and safety of their research.
The Darly Solutions development team created a platform for the client that can achieve 99.9% accuracy in clinical diagnostics. To achieve such impressive results, we used the following technology stack:
- Python for machine learning and data analytics;
- JavaScript and React for creating an intuitive user interface;
- WordPress for backend development.
We successfully implemented predictive tools, high-quality data visualization, and a user-centered UI/UX design in the diagnostic solution. As a result of our collaboration, the client’s goals were met. The company received a flexible, scalable, and highly efficient system.
Conclusion
It can be confidently stated that machine learning projects in the medical field are the future of global healthcare. Intelligent solutions have the potential to revolutionize disease diagnosis and treatment, patient care, and drug development.
Do you want to follow the latest trends and provide the highest quality services? Now is the perfect time to find an expert team to develop an AI and machine learning-based medical application.
The Darly Solutions team is ready to assist you with this! Contact our manager to discuss the project details and receive a digital solution that will exceed all your expectations.

COVID-19 marked a turning point for digital health. In fact, it made mobile medical apps mainstream in healthcare. According to Statista, as of 2025, the Google Play Store had over 36K healthcare apps, and the Apple App Store had over 35K. These apps cover telemedicine, fitness, wellness, mental health, nutrition, and pharmacy delivery, competing for users' attention and digitalizing the traditional healthcare industry.
Since development isn't just about coding, it requires complex regulatory navigation, technological and market demands, and strategic investment.
The cost of developing a health app will vary depending on what kind of app you want to launch. In fact, all types of eHealth apps, from telemedicine, fitness and wellness, mental health, and nutrition planning to pharmacy delivery apps — are getting great traction in the market today.
In this article, you will learn what affects the cost of developing a healthcare mobile app.
Healthcare Apps Market Overview
The mHealth app sector demonstrates skyrocketing growth driven by evolving healthcare delivery models. According to Grand View Research, the global healthcare app market will grow at a 14.9% CAGR through 2030. This growth is due to increased smartphone use for health tracking, the rise of AI assistants, and a demand for remote, patient-centered care.
Advantages of Developing a Healthcare App
Digitalization and automatization run the world, and healthcare thrives here the most. Since patients can now reach doctors with a few clicks, digital monitoring and telemedicine cut care costs by 25%.
About 63.4% of U.S. adults use mobile health apps, with many relying on them daily for fitness and wellness tracking. Additionally, a survey showed that 59% of participants have 1-3 health-related apps, which highlights even more significance of healthcare apps.
And the benefits don't end here. Dive with us into some of the other top benefits of healthcare apps:

Improved Patient Engagement
mHealth apps lead to better patient outcomes. With remote monitoring and reminders, they provide direct communication with providers and offer personalized health management tools.
Patient Customization and Tailored Treatments
Custom mobile apps streamline access to patient records. They help doctors create personalized treatment plans, improving outcomes and patient-provider relationships.
Medication Adherence Support
Medication reminders and tracking tools within these apps promote adherence, empower patients, enable timely provider intervention, and improve the management of chronic conditions.
Health and Fitness Tracking
Real-time data fosters proactive wellness and motivates users to achieve their health goals. Sharing this data with healthcare providers facilitates personalized care and timely interventions.
Analysis of Patient Behavior
These apps track patient behavior, including mood, medication use, and lifestyle choices. Real-time feedback lets doctors adjust their plans. Improved communication boosts patient engagement and outcomes.
Real-Time Global Collaboration
These apps break down geographical barriers and enable global healthcare teams to collaborate on personalized treatments. Continuous patient monitoring enables prompt intervention, fosters proactive healthcare, and raises global care standards.
Emergency Services Integration:
Healthcare apps with emergency services let users quickly contact help, share their location, and get help in emergencies. This approach improves response times and can save lives.
Reduced Diagnostic Errors
mHealth apps enhance diagnostic accuracy and patient safety. Intelligent tools support better decision-making, while predictive features help identify potential drug interactions and other adverse events.
Secure and Convenient Payment Options
Integrated payment gateways enable seamless transactions via credit/debit cards or PayPal. Automated notifications and easy access to payment history streamline billing and enhance patient satisfaction.
Efficient Data Management
Using AI and blockchain in mobile health apps improves data management, streamlines processes, and enhances doctor-patient communication. This approach leads to more personalized treatment and better health outcomes.
Types of Healthcare Apps and Their Development Cost
In this section, we'll look at the average cost to build a healthcare app across various categories.

Telemedicine App
Telemedicine is a synonym for modern healthcare. Now, healthcare professionals are at the fingertips and available from the comfort of home. From virtual consultations to video calls, the possibilities are vast.
Check for key components, cost, and timeline of the app deployment below:

Health and Wellness Tracking App
Given the vast and growing market, launching a wellness app is a promising venture. Look at the success of Headspace and Calm. They help many users find a sense of calm every day. Wellness apps typically include features like meditation, mindfulness practices, and productivity tools. With AI-powered nudges, you can help users stay mindful and re-energized.
Inspect the key aspects, budget requirements, and timeline for deploying the app below:

Medical Networking App
These platforms harness the power of the Internet to foster connections and collaboration. Healthcare providers can use these apps to expand their knowledge and share important information with respected colleagues.
Below, we've listed the app's features, financial estimates, and launch timeline:

E-prescription Apps
E-prescription apps are reshaping the prescription process, blending security with efficiency. They allow healthcare professionals to prescribe precise dosages, which pharmacies receive in real-time. This seamless flow ensures that medications are delivered right to patients' homes, making healthcare as easy as a tap on the screen.
Here's a detailed look at the app's features, cost projections, and expected timeline.

Hospital & Clinics Management Apps
Hospital and clinic management apps simplify administrative tasks, improve resource allocation, and boost overall efficiency in healthcare settings.
Below, we've detailed the app's features, pricing estimates, and launch schedule.

Chronic Disease Management Apps
Chronic disease management apps help users track symptoms, manage medications, and communicate with healthcare providers.
Take a closer look at the app's features, estimated costs, and projected timeline.

Appointment Scheduling Apps
Healthcare appointment scheduling apps make booking and modifying appointments easier, which improves patient satisfaction.
The app's primary functions, projected costs, and deployment timeline are listed below.

EHR/EMR Systems
Modern healthcare demands secure digital record systems. Blockchain EHR platforms protect sensitive patient data while facilitating doctor-patient communication. Smart contract automation streamlines medical workflows.
Check the app's core functionalities, expected expenses, and rollout schedule below.

Remote Monitoring Apps
Remote monitoring apps provide real-time insights into patients' health metrics, empowering healthcare professionals to act swiftly. This seamless connection ensures timely interventions, making healthcare more responsive and effective.
See the app's features, financial estimates, and launch timeline below.

Medical billing and coding
Medical Billing means submitting and following up on claims with health insurers to get paid for services by healthcare providers. It also includes verifying patient insurance, processing payments, and managing accounts receivable.
Medical Coding turns healthcare diagnoses, procedures, and services into universal alphanumeric codes. Accurate coding is crucial; it directly impacts billing accuracy and claim approvals.
If speaking to the real-world case, the hospital tracked underpayments and payer performance by implementing the billing system, boosting patient collections from 5% to 22-26%.
Key Features of Medical Billing Software
- Patient Record Management.
Efficient management of patient records eliminates manual filing and ensures quick access to necessary information.
- Medical Coding Automation.
The software supports standardized coding systems like ICD-10 and CPT to automate the coding process and reduce claim denials due to errors.
- Payment Processing Integration.
Integrated payment processing capabilities allow secure online payments via various methods, enhancing patient convenience.
- Financial Performance Analytics.
Tools for generating reports on collections, rejections, and overall financial performance help healthcare providers analyze their revenue cycle.
- Electronic Health Record Synchronization.
Seamless integration with Electronic Health Records (EHR) systems consolidates data accurately, improving workflow efficiency and reducing billing errors.
Steps in Developing Medical Billing Software
Developing medical billing software requires a strategic approach. It must balance technical complexity, compliance with regulations, and a user-centric design. This process involves planning, skilled development, and rigorous testing to meet healthcare standards.
Define Requirements.
Clearly outline the functionalities needed based on user feedback and technical specifications.
Software Development.
Engage a team of developers to create the software, focusing on design specifications, security considerations, and compliance with regulations like HIPAA.
Testing.
Conduct thorough testing to ensure functionality meets compliance standards and is free from technical issues before deployment.
Formula to Calculate Medical App Development Cost
The final estimate of your healthcare mobile app development cost relies on the duration of your project. However, you can calculate the approximate cost using the formula for the healthcare app development cost:
The hourly rate is the cost charged per hour of work, and development hours account for the total time used in the process.

Note!
The hourly rates depend on the skills and location of the app developers. If you have an offshore team, you might gain some cost advantages. Yet, skilled professionals might charge higher fixed prices. You must balance expertise and budget to get the best app development value.
Cost Per Feature in Healthcare App Development
The cost of healthcare app development is the cornerstone. Each added feature impacts the overall budget. For instance, user authentication can cost $2,000 to $5,000. Telemedicine features may cost $10,000 to $15,000. User-centric options, like appointment scheduling, cost $1,000 to $3,000 each. Strategic planning is essential to manage costs effectively.
Let's take a closer look at the price of each feature:

Cost Per Hour for App Development By Region
The hourly rate for healthcare app development isn't set in stone; it varies widely based on several key factors. They involve the app's complexity, the developers' expertise, their location, and the project's scope.
Here's a quick guide to typical hourly rates across different regions:
North America (USA, Canada): $100 – $250
The rates in North America are among the highest globally due to the high demand for skilled developers and the cost of living in major tech hubs like Silicon Valley. Senior full-stack developers can charge between $150 and $200 per hour.
Western Europe (UK, Germany, France): $80 – $200
This region has high rates due to a strong demand for skilled developers and a robust business environment. Countries like Germany and the UK typically charge between $22 and $90 per hour for developers, depending on their experience level. The average salary for software engineers in Western Europe ranges from $60,000 to $95,000 annually.
Eastern Europe (Poland, Ukraine, Romania): $40 – $100
Eastern Europe offers a competitive balance of cost and quality. The average hourly rate is lower than in Western Europe, with many skilled developers available between $24 and $46 per hour. With strong technical education and a growing IT workforce, Poland and Ukraine offer readily available development talent.
Asia (India, China, Philippines): $20 – $80
Asia generally offers the lowest rates for software development. However, quality can vary widely among developers. Rates typically range from $10 to $80 per hour. It is crucial to thoroughly vet developers in this region to ensure quality and reliability.
Australia and New Zealand: $80 – $150
Developers in Australia and New Zealand command higher salaries due to the high cost of living and demand for skilled labor. Average hourly rates range from approximately $50 to $150, depending on experience and specialization.
South America (Brazil, Argentina): $30 – $100
South America presents competitive rates with a growing pool of talented developers. Hourly rates typically range from $20 to $100, making it an attractive option for companies seeking cost-effective development solutions while maintaining quality.
Hidden Expenses in App Development
When planning a budget for mhealth app development, don't forget to account for these additional costs:
- Project Management: Usually adds 10-20% to the overall medical app development cost.
- Design: UI/UX design rates typically range from $50 to $150 per hour.
- Testing and QA: Costs generally fall between $30 and $100 per hour.
- Maintenance and Support: Ongoing expenses after launch are often billed at the same hourly rate as development.
Note!
These approximate figures may fluctuate based on your project's specifics and development team.
Legal and regulatory costs
Legal and regulatory healthcare app development costs can range from $5,000 to $15,000 annually. This covers compliance with key regulations like HIPAA in the U.S. and GDPR in Europe. These costs include fees for obtaining certifications, conducting privacy audits, and ensuring compliance with evolving legal standards. Developers must also consider the costs of data protection. They may need to consult lawyers to navigate complex regulations.
What Affects the Healthcare App Development Costs?
Healthcare software solutions come with different price tags. For example, an EHR system may cost $10K to $250K, while telemedicine platforms can range from $40K to $400K. What factors contribute to these costs? We're here to explain.
Scope and complexity
Healthcare app development costs hinge on project complexity. Advanced features like AI-powered decision support, analytics, and device integration drive up expenses and development timelines. Precise project scoping is critical: it minimizes unexpected costs and ensures optimal resource allocation.
Regulatory compliance
Protecting patient data via HIPAA compliance is non-negotiable, as it entails trust in healthcare services overall. However, it often comes at a cost: increased development complexity, higher expenses, and the added overhead of certifications impact both — budget and time to market.
Integration requirements
System compatibility drives up healthcare software development expenses. For compatibility and seamless data transfer, developers must invest substantial effort in connecting new software with legacy Electronic Health Record (EHR) and Electronic Medical Record (EMR) systems. The integration process becomes more complex when incorporating third-party services like payment platforms, telehealth tools, and laboratory information systems, dramatically increasing both development and testing costs.
Technology stack
Cross-platform software development multiplies costs. Creating separate codebases for web, iOS, and Android platforms can exponentially increase development expenses. Moreover, integrating cutting-edge technologies like AI and blockchain requires rare expertise, significantly inflating development costs.
Development team composition
Healthcare app development costs depend on the team structure. An in-house team may provide more control, while outsourcing to a third-party vendor can be more cost-efficient with proper management. Remember that specialized skills, such as cybersecurity experts and data scientists, are usually more expensive.
Design and user experience
Design determines healthcare software success. While a high-quality, user-friendly design may increase initial healthcare app development costs upfront, it drives better adoption and satisfaction in the long run. Features for disabled users will have higher design and development costs. Major expenses come from thorough research, testing, and iterative development.
Testing and quality assurance
The smooth operation of healthcare software depends on regular testing. In-depth testing for functionality, security, compliance, and performance raises healthcare app development costs due to the lengthy cycles involved. Feedback from real users during testing further raises the overall project expenses.
Maintenance and support
Healthcare software expenses don't end at development. Maintenance and post-launch support (e.g., bug fixes, updates, regulatory compliance changes) demand ongoing investment. Additionally, providing user support services adds to overall operational expenses.

These factors guide informed decisions on scope, technology, and resources for healthcare software development. Plus, they empower effective budgeting and cost management, often resulting in successful healthcare software development initiatives.
Best Practices for Cost-Efficient Healthcare App Development
Deployment of healthcare apps is an expensive process. Sometimes, it squishes the expenditures; software integration expenses range from $20,000 to $100,000, while regulatory compliance adds $20,000 to $80,000 to development budgets. These substantial costs necessitate strategic financial management.
Smart business owners seek smart moves to keep healthcare app development costs under control. Here are some options available in detail:
Opt For Cross-Platform Development Tools.
React Native and Flutter can cut your budget by up to 1.5 times through a shared iOS and Android codebase. In addition, source code from a cross-platform mobile app can be repurposed to create a web application.
Leverage Off-the-Shelf SDKs and Code Libraries.
Businesses can use existing solutions and customize them to fit their needs instead of building common features from scratch. Pick a ready-made option and modify it to fit your specific needs.
Consider White-Label and No-Code Solutions.
Branded and system-integrable off-the-shelf products provide a cost-effective way to roll out services like telehealth. This white-label product integrates with your digital systems, like practice management platforms. It lets clinics cost-effectively start telehealth services using no-code solutions.
Conduct Rapid Prototyping.
Before diving into full development, opt for prototyping. This stage can help validate your ideas and test the UI/UX while cutting unnecessary costs.
Employ a Multidisciplinary Team.
Hire a full-stack team that includes in-house talent in design, development, QA, etc. Clearer, more concise communication keeps mHealth app development costs under control.
Outsource Smart.
Outsourcing holds potential as a strategic solution yet demands careful evaluation before proceeding. Combining medical app development intricacies with cultural misunderstandings can produce a product that fails to fulfill expectations. The cost of healthcare app development in the USA mirrors its distinct challenges and established standards.
Involve in the Development Process From the Start.
One of the greatest mistakes is to hire an experienced team and then leave to manage themselves. Make the feedback a routine, and maintain communication with the development team throughout the process. If you lack time and material — hire a dedicated project manager. Make sure your reliable partner maintains regular updates with you.
Conduct Thorough Testing.
QA is on your development partner. Nevertheless, you can also verify stuff on your end. Early detection of bugs simplifies their resolution while keeping costs low. To prevent old errors from recurring, developers should conduct retrospective tests.
Implement DevOps Best Practices.
Without appropriate DevOps practices, developers lose valuable time. Automated DevOps systems allow developers to focus on writing code features rather than spending time on manual quality assurance and releases.
Optimize Maintenance Costs.
Long-term maintenance costs decrease when automated platforms track issues and collect user feedback.
Prioritize Features Wisely.
Start with core features before building a Minimum Viable Product (MVP), enabling market testing before further development.
Regulatory Compliance For Health Apps
Developing medical applications requires strict adherence to international data protection standards. These regulations safeguard patient information and ensure legal compliance across global markets. Here's a comprehensive breakdown of key regulatory frameworks:
1. European Union: GDPR (General Data Protection Regulation)
Coverage: Patient health records and personal data
Key Features:
- Mandatory data breach reporting within 72 hours
- Patient right to data access and deletion
- Requires explicit consent for data collection
Fines: Up to €20M or 4% of global revenue
2. United States: HIPAA (Health Insurance Portability and Accountability Act)
Coverage: Protected health information (PHI)
Requirements:
- End-to-end data encryption
- Access control mechanisms
- Audit trails for all data access
- Regular security assessments
Penalties: Up to $1.5M per violation annually
3. Canada: PIPEDA (Personal Information Protection and Electronic Documents Act)
Coverage: Private sector data handling
Key Requirements:
- Explicit consent for data collection
- Purpose limitation
- Data accuracy maintenance
- Security safeguards
Penalties: CAD 100K per violation.
Tech Stack For Healthcare App Development
Discussing the tech stack goes first, right before answering the ultimate question of how to develop a health app. Also, will the dev work blow the budget?
Since the health app's tech affects its performance, convenience, and company expenditures. Here are some common tech stacks for mhealth app development used by the Darly Studion team:
Programming Languages:
Java, Python, C#, C++, JavaScript, PHP, and HTML5.
The choice of specific language depends on the functionality you need. If the app stores and analyzes large data or uses AI, choose Python and Java for the backend and JavaScript for the front end.
Operating Systems:
Windows, macOS, Linux, and mobile Apple iOS or Google Android.
Here, we just need to choose a trustworthy provider with great support. We choose an OS with strong security and top performance.
Databases:
MySQL, Oracle, PostgreSQL, Memcached, and MongoDB.
To select the best database or a mix, contact a development team. They will evaluate your data type, volume, and request frequency to guide you in choosing the right database size and provider.
Servers:
Apache server and NGINX.
These two options lead the market, but their HIPAA compliance is most important to us.
Other useful tools:
- DevOps tools: GitHub, Jenkins, Selenium, Rollbar, or Bitbucket.
- Business tools such as Slack and G Suite — for communication and management.
- Tools like Google Analytics for tracking, Stripe for payments, and Elasticsearch for search enhance functionality.
- Cloud storage and hosting providers such as Amazon S3, Amazon EC2, or DigitalOcean.
Now that we've covered the technology stack for healthcare apps let's break down the next practical steps.
Design for Healthcare App Development: Best Practices
Creating effective healthcare applications requires meticulous attention to design principles that balance clinical utility with user experience. Studies show that 93% of physicians believe mobile health apps can improve patient care, while 80% of users abandon healthcare apps within the first 2 weeks due to poor design.
User Interface Design
Medical professionals spend an average of 4.5 hours daily interacting with healthcare interfaces. Design must accommodate the 15-second average attention span during critical care scenarios, with interfaces allowing task completion within three clicks or less.
Visual Elements
- Color schemes with a minimum 4.5:1 contrast ratio (WCAG 2.1 standards)
- Typography: 16px minimum for body text, 24px for headers
- Maximum of 6-8 core icons per screen to prevent cognitive overload
- 95% of users expect consistent branding across all touchpoints
Functionality Considerations
- Critical features accessible within 0.8 seconds
- The data visualization comprehension rate should exceed 90%
- Forms designed to reduce error rates below 1%
- 99.9% uptime for offline critical functions
Security Measures
- 2-factor authentication reduces breaches by 99.9%
- 256-bit AES encryption ensures the security of data at rest and in transit
- HIPAA compliance requires 72-hour breach notification
- Monthly security audits covering 100% of the codebase
Accessibility Features
- Voice commands with a 95% accuracy rate
- Screen readers supporting 40+ languages
- Text scaling from 100% to 400%
- Regional support for 25+ major healthcare markets
Performance Optimization
- Page load times under 3 seconds (Google's benchmark)
- Data sync completion within 5 seconds
- Maximum 5% battery drain per hour of active use
- 99% crash-free sessions rate
Testing Requirements
- Minimum 500 hours of user testing with healthcare professionals
- 100% compliance with ISO 13485 medical device standards
- Testing across 15+ device types and 5+ operating systems
- Weekly security scans covering 50+ vulnerability types
Key Metrics for Success:
- User Retention: Target 70% after 30 days
- Task Success Rate: Minimum 95%
- Error Recovery: Under 5 seconds
- System Response Time: Under 0.1 seconds
- User Satisfaction Score: Above 85%
Healthcare Application Development Steps
Crafting a custom medical software development service demands mastering five non-negotiable development stages:

Step 1. Shape the concept for your app
Before writing a single line of code, decode the fundamental value proposition, transforming your app from a mere download to a user's daily digital health companion.
Decode your audience's DNA.
Segment users by age, location, and average income. Analyze their needs to create a value proposition that challenges industry standards.
Conduct market research.
Identify the strengths and weaknesses of your target market. Benchmark against competitors and develop a unique value framework.
List selling points.
Create a comprehensive list of features and additional services that will appeal to your target audience and encourage them to choose your mhealth app.
Define your goals.
Clearly outline the objectives you want the app to achieve and align them with your budget for effective planning.
Step 2. Choose the monetization model
Basically, there are six monetization business models for healthcare apps, from freemium to paid-in-app. This aspect is pretty simple for healthcare providers who decided to build a healthcare app as another platform to sell their services.
Healthcare providers who use healthcare apps to sell their services will find this aspect straightforward because they don't need to generate revenue from the app, which functions as an additional tool. However, the question is a bit more complicated for owners of apps such as meditation or healthy lifestyle platforms.
Step 3. Create UI/UX design
In this development phase, UI/UX designers establish the app's functionality and visual design while managing platform branding when necessary. The most time-consuming task during this stage remains developing prototypes that include visual mockups for each app screen and user interaction.
Another crucial part of the design process is selecting fonts, color schemes, and button placement. mHealth platforms must prioritize responsive design across all devices while ensuring users can reach their goals efficiently.
Step 4. Build an MVP
Even if you lack the necessary funding to implement your ideas today, that doesn't mean you cannot begin developing your project. That's what an MVP is for.
MVP creation enables faster launch and collection of initial user feedback. As your app develops, you can raise more funding. This will help expand its capabilities. An MVP approach cuts financial risk since it requires less investment to test a product's viability before committing further.
Step 5. Collect feedback and update
Typically, at this stage, QA engineers perform another round of testing after developers deploy updates to ensure that there are no bugs and that project requirements match the results.
Timeline of Custom Healthcare Software Development Services
The timeline for custom healthcare software development varies according to the complexity, scope, and specific requirements. Let's explore the general phases involved.
Initial consultation and planning.
This phase starts by engaging stakeholders to clarify their needs and objectives. It then lays down the scope, key features, and deliverables, resulting in a high-level timeline and budget. The project team then defines roles and responsibilities. This process typically takes two to four weeks.
Research and analysis.
The research and analysis phase starts by analyzing market trends and examining competitors' healthcare software solutions. The next step is gathering insights through surveys and interviews with potential users. The technology stack, third-party integrations, and compliance requirements are evaluated at this stage to ensure thoroughness. This vital phase will take three to five weeks and lay a solid foundation for your project.
Designing phase.
The design phase usually spans four to eight weeks. At this phase, create wireframes and prototypes for key screens and user journeys to develop a user-friendly interface. Additionally, conduct a usability test. Every detail must shine.
Development phase.
This phase lasts 12 to 24 weeks. It focuses on building the software's core: the backend, the front end, and key features like patient records, scheduling, and billing. The backend includes the databases and APIs. The front end must be user-friendly. Plus, robust security measures are integrated, including HIPAA and GDPR compliance.
Testing.
Before release, the software undergoes a 6 – to 10-week testing cycle. This includes unit tests, integration tests, performance tests, security tests, and user acceptance tests, which help ensure the software performs well and is secure.
Deployment and training.
The deployment and training of your healthcare software will take three to six weeks. At this phase, developers ensure the software works well, that any early issues are fixed quickly, and that the app is user-friendly.
Must-Have Features of Healthcare Apps
The type and main function of a healthcare app dictate its features. Yet, there are the most common that mHealth apps share, whether for telemedicine, hospitals, or urgent care. Here are the essentials:
- Sign-up / Sign-in. While in-app registration might require hefty user details and time to figure everything out, the sign-in process should be swift and easy. For a smooth experience, allow users to sign in with their email.
- Doctors' and patients' profiles. Doctors' profiles should display their specialization, education, current workplace, and availability. Patients' profiles must include their medical history, prescribed medications, and other key health details to ensure a seamless interaction.
- Appointment management. The calendar feature helps doctors track appointments and allows patients to browse available slots to book visits. A seamless experience for everyone involved!
- Push notifications. Designed for both healthcare workers and patients, these features act as reminders for upcoming appointments and medication alerts.
- In-app chat. With in-app chat, users can easily connect with healthcare managers or doctors. It enables faster communication, making healthcare more accessible and efficient.
- Video consultations. The shift to video call appointments came as a safer alternative during the pandemic when in-person consultations posed higher risks. Now, this option saves time for doctors and patients and lowers the chance of spreading illnesses.
- EHR integration. Each medical visit or procedure adds to a patient's treatment history, stored in an EHR (electronic health record) system. Including an EHR system in your app is vital for delivering the best care and streamlining the process for future healthcare providers treating the patient.
- E-prescriptions. As consultations move online, doctors should also be able to prescribe medications digitally, which cuts time waiting in key and frees up doctors' time. Another benefit is that e-prescriptions are more secure and difficult to forge.
- Payment gateway. Paid medical services go hand in hand with in-app payments. Thus, opt for payment gateways that accept credit and debit cards, digital wallets, crypto payments, and other alternative methods.
- Ratings and reviews. Designed for patients, this feature simplifies selecting a trusted professional who fits their specific requirements.
Challenges in Healthcare App Development
Healthcare app development faces several challenges that can hinder progress.
Non-Compliance with the Law.
HIPAA and FDA regulations safeguard personal data and guarantee the safety of products. Failure to follow these rules leads to financial penalties and the erosion of trust. To ensure compliance and avoid penalties, businesses must consult legal experts.
Lack of Security.
Hackers can quickly access sensitive data, such as customer information or financial records, when business security systems fail. Businesses can suffer reputational damage and financial losses due to this. To prevent this, businesses must improve their security and work with tech experts.
Presence of Multiple Channels and Devices.
Multiple channels and devices present integration challenges since they operate on unique systems and protocols while meeting different requirements. Differences between technology standards and data formats trigger compatibility problems that need additional effort to fix.
Marketing and Launch Cost of Healthcare Application
Depending on scale and strategy, a healthcare app's marketing and launch costs can range from $5,000 to over $100,000. Key cost components include:
- Market Research: $5,000 to $15,000 for analyzing market needs and competition.
- Launch Campaigns: $5,000 to $100,000 based on scope and platforms.
- User Acquisition Costs: Cost per install (CPI) ranges from $1.42 to $3.75, varying by advertising platform (e.g., Google Ads, Facebook Ads).
Effective budgeting is essential for a successful launch and user engagement.
Business and Monetization Models of Healthcare Apps
Since healthcare thrives on digitalization, many people have at least one app on their devices. However, the competition for user attention takes high stakes. The question arises: How can we promote and monetize mhealth apps?
Below, we have listed some of the most common business and monetization models:
Freemium Model
The freemium healthcare app offers a basic version and charges for premium features like advanced health evaluations. This model promotes rapid market penetration and attracts a large user base. In the long run, it drives sustainable revenue by converting a percentage of free users to paid tiers.
Subscription Plans
Subscription models work best for healthcare apps offering ongoing value. Tiered pricing can include basic tracking features, fitness coaching or telehealth services, access to a library of health articles, and premium telemedicine services with personalized health plans. Before enroll this model, ensure its pricing reflects the app's unique value proposition.
In-App Purchases
Even though it has a complicated deployment architecture, it is an incredibly lucrative way to monetize the app. In short, this model helps to upsell extra features or content within the app. Thus, users can purchase in-app items such as extra lives in games, extra workouts in fitness apps, or pre-paid visits and prescriptions in mhealth apps.
Also, businesses often sell branded merchandise or partner with other brands via in-app purchases to promote themselves more.
Telemedicine Consultations
The pandemic marked the popular era of telemedicine. Now, many apps offer video consultations with subscription plans or pay-per-consultation fees. However, the healthcare specialists' credentials and licenses are the most important. They are the foundation of brand trust and revenue.
Advertising and Sponsorships
Healthcare apps monetize through strategic sponsorships and expert content. Targeted advertising creates win-win partnerships. It lets companies reach specific audiences and generate app revenue.
Partner with medical experts to create credible content, like articles and videos. This strategy will boost the app's credibility, expand its reach, and diversify revenue.
Pay-per-usage Model
The pay-per-usage model, common in SaaS, is now being implemented in healthcare apps. This cost-effective approach allows users to access healthcare resources and pay only for their actual usage, avoiding the commitment of a subscription. Which often results in user trust and brand loyalty.
These models can be mixed and matched depending on the target audience and specific functionalities of the healthcare app. However, first things first, robust business and monetization require a consistent content publishing strategy and tools to publish high-quality medical content regularly.
Healthcare App Development in a Nutshell
Indeed, healthcare apps are transforming digital health with more accessible and intuitive tools. From telemedicine and health trackers, the healthcare app development cost varies by type, scope, team, and overall business aim.
But the truth is one. Building a successful mobile health app requires strategic planning, research, and expertise in medical software development combined with a significant investment. This is especially true since medical app development costs go beyond initial creation, including planning, regulatory compliance, and ongoing maintenance.
Effective apps demand resource management and collaboration with experienced teams. A smart approach can help businesses develop impactful solutions that benefit both patients and healthcare providers.
Partnering with Darly Solutions enables companies to create healthcare apps that meet technical standards while delivering real value in digital health.
Build Your Healthcare Application With Darly Solutions
From market analysis to launch, Darly Solutions uses a strategic 5-step process to build high-quality healthcare mobile apps tailored to your audience. Follow us:
- Market & User Analysis: We help you understand your target audience (patients, doctors, etc.) and analyze existing apps to identify opportunities.
- Planning & Business Analysis: We collaborate with you to define the app's concept, business goals, technology, and resources, ensuring alignment with your strategy.
- Design & Prototyping: We design user-friendly interfaces and develop prototypes to validate requirements and gather feedback.
- Development & Testing: Using Agile methodology, we build and rigorously test the app in iterative sprints.
- Release & Support: We handle app store publication system integration and provide ongoing maintenance and support.
For now, don't settle for less. Darly Solution is here to help! Reach out today to discuss your project in detail.

With the global aging population and the rise of chronic diseases, the remote patient monitoring market is booming as ever. From 2023 to 2024, it grew from $30.97B to $36.31B. And it won't stop here. Insider Intelligence predicts 70.6M US patients will use software for remote patient monitoring by 2025.
We can't overstate the importance of remote patient monitoring software. Such apps improve access to care, reduce hospital readmissions, and help save up to 60% on hospital visits, which results in higher-quality treatment in the comfort of patients' homes.
And benefits don't end up here. With ongoing digitalization via IoT and modernization of the healthcare system, don't wait for the best time for remote patient monitoring software development. The best time is now.
We've detailed remote patient monitoring apps below and covered their benefits, architecture, and top examples. You'll also see how Darly Solutions crafted an app for the health tech company. Read on, and stay tuned.
RPM monitoring software — is a digital tool for wearables, mobile apps, and medical devices that collects, analyzes, and shares patient data with medical personnel. Heart rate, blood sugar, and oxygen levels are among the most vital metrics. RPM software scores help catch health issues early, manage chronic conditions, and aid post-operative recovery.

How remote patient monitoring software works
From heart rate to blood glucose, each RPM system is designed to monitor a specific aspect of the body. However, elements included in any remote patient monitoring software development are typically the same. This is how the RPM system works:
- Collects and exchanges data.
Once calibrated, the devices send the data from the patient to the provider. The devices must have a Wi-Fi or LTE adapter for successful transfer. The data can also be sent via Bluetooth to IoT mobile apps via RPM devices. - Centralizes storage.
The provider securely stores the data collected from various sources, including patient devices, analytics systems, and e-medicine.
- Analyze.
The data is processed using advanced AI for management and analytics. Alerts are sent to caregivers, providers, and patients as needed, per their preferences. - Broadcasts.
Remote monitoring systems become telemedicine platforms when integrated with communication features like video conferencing, simplifying doctor-patient interaction.
- Sends emergency notifications.
When doctors identify health issues requiring daily monitoring, they oversee the data collected by the RPM system. Notably, it can notify emergency services if a patient needs urgent care. For non-urgent cases, patients can receive instructions for the next steps. However, HIPAA and similar regulations may restrict including sensitive patient information in certain notifications to protect privacy.
Why build remote patient monitoring software? Key advantages
Nevertheless, the RPM is part of the broader automation revolution; it has universal healthcare benefits overall. Let's examine the main of them:
Better access to health services
With remote patient monitoring software, medical services have no geographical boundaries. Patients can get timely medical attention at home and manage their health, fostering a greater sense of control under health conditions.
Improved patient outcomes
A study found that RPM cut hospital admissions for chronic care complications by 19% to 41%, which results in improved patient outcomes.
Cost-effective care with reduced readmissions
The average cost of hospital readmission is about $15,200, which makes the prevention of readmissions through remote patient monitoring software financially beneficial for both patients and providers. Even more, it is a well-established fact that early detection generally translates to lower healthcare costs.
Better client engagement and satisfaction
Over 94% of patients are satisfied with RPM's care. It sparks their curiosity about their health and boosts engagement. Such an increased sense of involvement often inspires commitment to treatment plans.
Early detection and timely intervention
The CDC reports that RPM can cut chronic disease complications by 40%. This highlights the need for swift intervention to reduce health risks.
Components of remote patient monitoring software
There is no one-fit RPM soft, as it differs in nature. However, each patient monitoring system generally has 3 to 5 basic components. Let’s delve into them:
Personal monitoring devices
From continuous glucose and heart rate monitors to blood pressure cuffs, digital scales, and peak flow meters.
Patient-side mobile applications
Prioritize user experience, making it easy for patients to access their health data. Additionally, they offer features like medication reminders and secure chats with healthcare providers.
Cloud database
Cloud repositories allow healthcare providers to store large patient data securely. They are scalable and accessible, adapting to growing datasets for long-term monitoring.
Hospital-side web app
These applications are part of hospital management software. They ensure compliance, enable integration, and support decision-making. Additionally, they offer reporting, notifications, and analytics to improve patient care.
Other modules
These comprise decision support systems, reporting tools, notification systems, and analytics platforms.
Essential features in remote patient monitoring solutions
Here are the essential features of a remote patient monitoring (RPM) solution:
Real-time tracking of patient vital signs
Wearable sensors, fitness trackers, blood pressure monitors, and glucose meters perfectly gather and handle real-time health metrics. Then, this data is sent to healthcare providers and added to Electronic Health Records (EHRs) for timely interventions and informed decisions preventing complications.
Intuitive interfaces and user-friendly features
Machines must be easy to set up, a breeze to wear, and simple to operate. Meanwhile, patients should access their data effortlessly through a smooth web or mobile app to track their progress. This connection allows seamless communication with healthcare providers, ensuring everyone's on the same page.
Accessibility features
Ultimately, create a system with all users in mind. Consider accessibility guidelines like WCAG and CVAA to pave the way for inclusive innovation. Encompass voice control for effortless data entry, navigation, and text-to-speech features to support people with dyslexia and other disabilities. Moreover, a patient-first design shines with screen reader compatibility, high-contrast modes, and a crystal-clear interface.
Personalized risk alerts and reminders
For swift and customizable alerts, the RPM system must adjust thresholds. For example, alerts can be sent when vital signs fall outside preset limits. This enables timely intervention to reduce the risk of adverse events.
Safe data transmission and storage
Patient data security is a top priority in remote patient monitoring software development. Thus, apps must comply with all regulations like HIPAA, as they protect the privacy and security of patient data and save from hefty fines.
Smooth EHR integration
EHR integration allows the automatic transfer of RPM data, giving healthcare providers access to complete patient histories for better decision-making and outcomes.
Reports and analysis of patient health data
Advanced analytics and reporting in remote patient monitoring software development provide valuable data insights for healthcare professionals (for data-driven decisions) and patients (to motivate healthier choices).
The architecture of a remote patient monitoring system
Remote health monitoring systems are designed with a multi-layered architecture. Basically, it has five core components that enable uninterrupted data flow within the system. Let’s break into the point of the whole structure:

Smart-connected sensors for health tracking
The sensor layer comprises remote monitoring devices such as EKGs, sleep trackers, smartwatches, and blood pressure monitors. Then, they transmit this data to the dedicated mobile app via Bluetooth or to the cloud via the Internet.
Patient interface
Patient-facing RPM apps collect real-time health data from connected medical devices, allowing manual entry of symptoms and medication intake. RPM apps often include data visualizations for tracking health trends and may have integrated telemedicine features, such as video conferencing for appointments, follow-ups, prescriptions, and virtual consultations.
Cloud RPM server
Cloud services form the core of RPM systems, providing secure storage, processing, and data analysis from devices and the RPM app. This engine also integrates with EHR systems to access patient health information (PHI) in FHIR format. It can identify trends, such as early signs of complications.
Medical staff dashboard
Patient data flows bidirectionally between the medical staff interface and the cloud RPM server, enabling effective management by care teams.
- Data visualization module.
Via charts and graphs that show trends in vital signs, medication adherence, and other data, the module gives providers a 360-degree view of the patient. - Alert management module.
The system promptly alerts clinicians to critical situations and device failures in real-time. - Reporting module.
The module generates custom reports on patient data, which hugely help track progress and gain insights over time. - Communication module.
This module has two-way messaging, video chat, and/or telephony integration and is made for secure, remote communication between clinicians and patients. - Appointment management module.
This module handles appointment scheduling and patient-provider communication, allowing both patients and providers to request appointments.
Depending on the organization's needs, a doctor-facing RPM interface can include other modules, such as patient management, care plans, and patient education.
Admin web panel
A key part of the RPM architecture is a control dashboard. It helps with admin tasks like configuring roles, managing patients, and setting alarms.
Remote patient monitoring software development: Key steps
Once you have a clear idea for your software product, find an experienced dev company to implement it. When contacting your tech partner, you don't need detailed software requirements. A high-level understanding of the functionalities is enough to get started for any custom healthcare software development services stages. Let’s break them down:

Step 1: Requirement collection and analysis
The process starts by refining your product vision. Then, define project goals based on the health conditions your RPM solution will address. Your team will then identify core functions, pick the best tech stack, and plan the app's architecture. If integration with systems like EHRs is required, your tech partner will ensure compatibility.
Step 2: Outlining security and compliance requirements
Remote patient monitoring software must follow HIPAA and FDA rules. The development team implements audit trails, encryption, secure cloud storage, and APIs for secure communication to ensure data security and privacy. They also define a testing strategy for the pre- and post-production phases.
Step 3: Prototyping and design
To create an intuitive, user-first staff interface, UX/UI teams conduct user research to define user personas and journeys. Based on this research, designers create a prototype reflecting both the initial vision and user needs, gathering feedback on the user experience. The team prioritizes a clean, engaging, and accessible design. Based on feedback, they will refine the prototype and send the final designs to the dev team.
Step 4: Development and integration
Tech experts will use best practices to develop your RPM system iteratively to meet regulatory compliance. This work may include front and backend components, patient and doctor apps, and integration of medical devices.
Step 5: Testing
When it comes to RPM development — thorough software testing is as important as the development itself. After testing, developers should prioritize IoMT device compatibility. They must also ensure smooth integration with the RPM system for the most stability.
Step 6: Ongoing improvements
After deployment, the dev team monitors and tunes the RPM system to meet business and tech needs. They provide training and support for patients and healthcare professionals.
Beyond monitoring and troubleshooting, your tech team will prepare a roadmap for software updates. This will enhance the system's features and security in the future.
RPM Software Deployment: Challenges and Practical Solutions
Let us explore the most notable challenges organizations encounter while deploying their RPM.
Regulatory compliance
RPM's compliance with HIPAA and GDPR relies on strong data security and privacy. It must meet standards like ISO 27001 and IEC 62304 for this.
What to do:
- Develop a comprehensive compliance framework according to all requirements like HIPAA, GDPR, FTC (Federal Trade Commission), FDA regulations, and more.
- Conduct regular audits and assessments outlining clear policies and protocols for staff.
- Provide ongoing staff training to ensure they are aware of their responsibilities.
Data security and privacy
Healthcare organizations handle sensitive patient data (vitals, medical history, personal details, reports, treatment plans). Unauthorized access poses the risk of data breaches and subsequent fines that could total millions of dollars.
What to do:
- Use encryption techniques of RPM-collected data, telehealth appointment recordings, and other sensitive patient health data.
- Implement strong authentication and role-based access.
- Regular audits and security assessments.
- Conduct employee and patient training.
- Adopt role-based access control (RBAC)
Technology integration and compatibility
Outdated systems may lack compatibility, hindering integration and impacting data accuracy and security. Integrating EHR and clinical systems can also be difficult, affecting data sharing and patient care. Ensuring interoperability for seamless data exchange adds another layer of complexity.
What to do:
- Assess current infrastructure compatibility.
- Follow interoperability standards and protocols.
- Adopt HL7 and FHIR standards.
Cost-benefit analysis
RPM implementation presents a cost-benefit challenge for healthcare organizations. While offering benefits like improved outcomes and enhanced care, the substantial upfront investment in hardware, software, infrastructure, licensing, staff training, regulatory compliance, and data security must be carefully weighed.
What to do:
- Conduct thorough cost assessments.
- Estimate ROI and potential cost savings.
- Strategically allocate resources.
Data precision and accuracy
Inaccurate data transmission from RPM devices (e.g., wearables) poses a significant challenge, potentially leading to misdiagnosis and compromised treatment. Several factors can affect data accuracy, including device calibration, signal interference, network issues, and device quality.
What to do:
- Choose quality sensors and wearables.
- Regularly calibrate devices.
- Implement quality assurance measures.
Lack of patient engagement
Some patients fear switching to modern healthcare and its tech just because they are used to in-person hospital visits. Thus, using the devices, checking vital signs, and messaging the doctor may be hard for the patients.
What to do:
- Prioritize a user-friendly interface.
- Craft tutorials for device usage and RPM data analytics interpretation.
- Incorporate gamification elements (e.g., badges, progress tracking) to incentivize engagement.
- Bridge language barriers for diverse patient populations by providing support in multiple languages.
RPM software development cost
The cost of developing Remote Patient Monitoring (RPM) software varies based on complexity, features, and the development team's location. Here’s a breakdown of the estimated costs associated with RPM software development:
- Basic RPM application ranges from $50K – $70K.
- Standard RPM software ranges from $100K – $400K or higher, depending on the specific requirements and features.
- Costs can be $500K or more for advanced solutions with complex systems and integrations.
Both building an in-house tech team and outsourcing software development come with significant costs: salaries/recruitment expenses versus hourly rates and vendor fees. Without proper research, you risk overpaying for a software solution — whether through in-house hiring costs or outsourcing fees — or settling for a product that doesn't meet your requirements.
To calculate the precise budget for your RPM software development idea — please fill out this form. We will contact you shortly.
Best RPM software
Here are some popular remote patient monitoring use cases that might inspire you for your own:
CoachCare
CoachCare was founded over a decade ago, now supports over 3,000 organizations, and serves over 150,000 patients. Boasting a remarkable RPM, it claims a success rate exceeding 95%. It advocates for RPM coverage and collaborates with groups like CMS and AMA. CoachCare's tech lets patients log vital health metrics via an app. Its simplicity boosts engagement. Experts recognize its support of the healthcare industry.

Healee
Healee is a health tech company founded in 2017, now handles over 700,000 visits per month, both onsite and virtual, and supports 5,000 physicians across 200 clinics. With EHR, e-prescription, and billing integrations, the Healee platform streamlines healthcare delivery in wellness, mental health, chronic care, and women's health.

Doctolib
Founded in Paris in 2013, Doctolib is a top healthcare booking platform. It serves over 400,000 providers and 50 million users. It handles 70 million monthly bookings in France, Germany, and Italy. It offers appointment scheduling, telemedicine, and patient messaging. These services reduce missed appointments by 60% and save doctors 1.5 hours per week on administrative tasks.

Senseonics
This company revolutionizes blood glucose monitoring. The system features a sleek, removable transmitter and a sensor expertly implanted under the skin by a healthcare pro. Connected to a mobile app, the sensor offers real-time insights, alerting patients through their smartphones or smartwatches when their glucose levels are too high. Sharing data with healthcare providers and family members becomes a breeze, ensuring optimal treatment strategies.
Currently, around 6,000 users benefit from the Eversense CGM system. By 2025, Senseonics aims to double that number.

Teladoc
Established in 2006, this Hoboken, New Jersey-based powerhouse is revolutionizing healthcare. With an extensive network of licensed professionals, HRS proudly claims the #1 spot in KLAS’ ‘Top Remote Patient Monitoring Companies’ from 2020 to 2023.
HRS offers its innovative PatientConnect platform, featuring over 90 tailored RPM plans for healthcare providers. Beyond monitoring, HRS embraces holistic care, providing behavioral health services like therapy and psychiatry, ensuring a comprehensive touch on every aspect of patient wellbeing.

Improving patient outcomes with RPM software: A case by Darly Solutions
In particular, the health tech company approached us about remote patient monitoring software development. They faced challenges with patient tech literacy, especially among the elderly. There was a risk of data overload for providers. Patient engagement was inconsistent. There was a need for system integration, like with EHRs. Plus, they had to ensure data privacy and security (HIPAA compliance).
Since the deadline was tight and there were a lot of high-precision requirements — we created a detailed plan for the project, assigned UX/UI design, web development, QA, and project management tasks, and pinpointed the tech stack.
Technology stack
We understood that choosing the right technology stack was crucial for success. After thorough consideration, we selected:
- Angular: For building dynamic web applications.
- HTML/CSS: For structuring and formatting the user’s interface.
- Docker: To streamline deployment through containerization.
- ngRx: For effective state management.
- TailwindCSS: To enable rapid UI development.
- NGX Pagination: For efficient handling of large datasets.
- JSON: For smooth and efficient data transfer between client and server.
Our efforts paid off. We launched the product on time, meeting all design, functionality, and quality standards. Our client now has a competitive product that is well-placed to thrive in the innovative telemedicine sector.

Read the details of the case here.
Wrapping up
Rising public interest, health concerns, and tech advances drive the RPM market to new heights in solutions and revenue. As we noted earlier, these technologies enable 24/7 health monitoring. They also provide remote populations with access to quality treatments.
Doctors, nurses, and other healthcare staff should focus less on routine, manual tasks in the next few years. They should focus on saving lives and providing treatment, which RPM can support perfectly. It can greatly reduce burnout and ease stress on global healthcare systems while driving market share to higher results and stakeholder benefits.
This is a great time if you're considering developing your RPM solution.

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The medical field has been developing for ages, but over the past twenty years, we’ve seen the flourishing of healthtech. And it’s not surprising: this technology is a game-changer for patient care, workflow, and life-saving.
The healthcare industry includes producing portable devices to monitor vital signs and online medical consultations provided by modern digital health solutions. And, similarly, every private clinic should have a top-notch website where patients can book an appointment with a doctor.
What are the roles of a medical site?
- A communication tool with patients. A site can be easily googled. Also, it contains information about available services and specialists. Thus, it makes it much easier for clients to reach out to you.
- A communicational channel. Internet marketing is one of the most effective tools for attracting customers, but you need a web resource to use it. Thanks to a site, you will be able to find customers among users of search engines and social networks.
- An image-maker of your organization. You need to give a good impression to make others want to collaborate.
- A source of getting feedback and statistical data. Thanks to analytics systems, you can track changes in behavioral factors, perform A/B tests, and monitor the effectiveness of various traffic channels.
So, a medical website must be very comprehensive, secure, and accessible at all hours. To achieve this, it’s important to involve specialists responsible for different aspects of the work at each stage of the healthcare website development.
Key Considerations When Hiring
Before you hire a health tech development company, it’s essential to ensure their team has the necessary hard and soft skills. The task of the dev team will be to make the site appealing to users and customize traffic channels. In turn, the site owner should provide the essential information and approve tasks in time to avoid excess of the final healthcare website development cost and pauses in the work process.
What should you bear in mind while searching web development companies for healthcare?
- Relevant experience. The more projects related to medicine they have, the better.
- Technical knowledge. Find out if the developers know the required programming languages.
- Communication skills. Website development is a team effort not just for the performers but also for the customers, so soft skills are vital here.
- Ability to comply with regulatory requirements. The company must know about HIPAA compliance and other legal provisions.
Experience in HeathTech
The company you want to hire must understand your business. That’s why your healthtech development company must be experienced with medical data and technology. Look for the company that has previously worked on similar projects. They could have a background in developing electronic health record systems, medical visualization software, remote care platforms, or other products related to healthtech website development. Companies with extensive experience in this field are well prepared to meet the specific demands of healthcare software development.
Technical Expertise
The company’s tech team should have certain skills required for medical website development. First of all, they need to ensure the security of the medical website. Secondly, it must be able to scale. This will allow you to upgrade a site following current changes like adding new services, functions, categories, or sections. It will also increase functionality and optimize it based on customer requests and company interests.
Another important aspect is defining the right tech stack. The developers must be able to choose a health tech website development programming language that meets business needs. The most popular ones are HTML/CSS, PHP, Python, JavaScript, Java, Ruby, and Swift. The final choice of one or another development tool must be made according to the goal of creating responsive web design and providing a brilliant user experience. The company should also have a skilled designer who can transfer your brand identity into the website’s UX/UI design.
Regulatory Compliance
A team working on a health tech site must guarantee its security as patients leave their personal data there – this can be ensured by its knowledge of how to create a secure website for healthcare providers. Specifically, such websites must meet HIPAA regulations and other confidentiality rules in health care, such as GDPR and PCI-DSS. Make sure the company is aware of these norms and can perform HIPAA-compliant website development.
Communication and Collaboration
Healthcare website development requires ongoing communication between the client and the contractor. For example, in the beginning, you and the tech team will negotiate on choosing the right CMS for the website. Consider hiring only those who are accessible, transparent, and timely. If there are no meetings or any other forms of communication, move on to the next candidates.
Partner’s Reliability
Make sure the chosen company is trustworthy. It must be present on social media and have its website with a portfolio. Seek for clients' feedback on special resources, forums, and social networks. This way, you’ll quickly see what prior customers have said about a company's service delivery. And, if some field-specific media have published case studies about the company’s work, it’s a very good sign.
Compliance with Your Request for Proposal
Once you decide on a candidate, it’s time to write a project proposal. Health tech website development proposals include stating the project’s objective, target audience, budget, and other features specific to your project. This way, the potential company will understand your business needs better and be able to provide an individual proposal.
Impression After Personal Interviewing
A key to successful collaboration lies in communication. Interviewing health tech web developers will allow you to test their understanding of your specific demands and the concept of the website.
Crucial moments to clarify during interviews:
- Ask for details about their experience. Get candidates to talk about a project related to health tech they have participated in. Go into detail to assess their role and expertise.
- Ask about the development process. Give them thorough questions to test their technical knowledge and figure out the workflow. You can also provide them with a test task to evaluate their skills firsthand.
- Uncover their management style. Ask if the team has worked on any cross-functional projects. Look for leadership qualities like guiding, empowering others to succeed, and handling conflicts constructively.
- Find out the team membership. Alongside those who are usually present in the technical team, such as engineers, QA testers, and tech leads, there should also be a UX designer.
- Ask who will own the code. It’s much better for you if the web development companies for healthcare offer a total handover. Yet, the agreement may include a clause that allows the contractor to keep the code. The worst thing that can happen might be that the company charges you more money because of the constant glitches they fix.
- Question what happens if the team fails to meet the deadline. Find out how the company can repay for the lost time.
Portfolio
Ask companies included in a shortlist to demonstrate their previous projects. A voluminous portfolio is usually a sign of a company that has extensive experience. This way, you’ll wind out what they’re capable of. The portfolio will show you if the team can manage challenging projects and meet high regulatory standards. Also, it will show how good and user-friendly their software is. And, naturally, pay strong attention to websites related to the medical field.
Conclusion
Ideally, a website solves several problems of a healthcare business at once. First, it is one of the most effective tools for attracting new clients. It also acts as a channel of communication with existing patients, forms the image of your organization, and allows you to get feedback and collect your customers’ data. All this is possible if the site is developed by the pros. That’s why you should be very picky when you want to hire a health tech development company. Follow the recommendations listed above to find the perfect fit.
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If you have a great idea, and it involves creating something innovative, aiming at solving standard problems using unconventional methods and tools, it’s probably worth bringing it to life gradually. This way, you will move from priority features to secondary ones, relying on real users’ opinions – both positive and negative ones. Actually, here, we described the essence of the MVP development process. Below, we will explain its definition and check its benefits and specifics of implementation.
Understanding MVP in Software Development
If you are going to build an MVP, you should first understand exactly what it is.
In a nutshell, a minimum viable product (MVP) is a product that has basic functionality to satisfy some needs of the target audience. Its main goal is to attract first users, determine their impression of interacting with it, and think through a further strategy for its development.
Key advantages of an MVP approach
When you decide to build MVP, you get the following benefits:
- Ability to confirm or refute hypotheses about the product
- Attracting investors through accelerated confirmation of the idea’s viability
- Help in analyzing the target audience
- Reduction of financial risks
- Development costs reduction thanks to proper prioritization of the product’s features
- Faster engagement of the target audience, long before the launch of a finalized product version
- Early bug fixing
- Reduced time to market
Thus, by resorting to MVP building, you can start to earn faster. At the same time, the development of a minimum marketable product is especially relevant for startups as it allows you to find out the real needs and pain points of your target audience in practice.
Developing Your MVP: Focus on Core Functionality
Now, let's find out what the MVP process looks like.
Identify your target audience
No matter how universal your solution is, its audience still has something in common, be it goals, pain points, demographics, or something else. Therefore, before you hone your product concept, you will have to define who it will be intended for – that is, conduct user research. To do this, you need to draw up a detailed portrait of the client – gender, age, place of work, hobbies, income level, desires, needs, problems, etc.
Come up with core functionalities
Surely, you have already seen a picture on the Internet that reflects the essence of MVP – a skateboard gradually turning into a car. Formally, this means that you need to understand which functions will be fundamental, that is, without which no user will be able to implement the task assigned to your product. These will be your MVP requirements. Then, as you receive reviews from real users, you can add features of less priority that make your solution more usable than the previous version.
Prioritize correctly
Before you start to develop MVP, think about which stages of your project are the most resource-intensive – they will need to be implemented first. As resources become available, you can assign lower-priority tasks to individual members of your team. Actually, this prioritization will determine your product roadmap. Thanks to this approach, you will eliminate downtime in your work processes and will be able to bring the MVP software launch date closer.
Define tools and resources
Finally, you should determine what tools you will use in development and what resources will be needed for this. We are talking about programming languages, wireframing and software development tools, platforms for project management, business messengers, etc.
Iterating Based on User Feedback
Any MVP strategy consists of iterations – that is, constant repetition of the development cycle based on user feedback received after testing its previous version. Let's look at the nuances of implementing these iterations.
Data collection methods
Depending on the resources available, you can collect data from real users by applying different methods. This could be live interviews, questionnaires, A/B product testing, supervised and unsupervised testing, and so on.
Feedback analysis and prioritization
Once the data has been collected, you will need to identify which reviews should be processed first and which ones can be postponed. In fact, everything is simple: the highest priority belongs to those that indicate that the user cannot perform the target action in your solution at all. Second in priority are reviews related to the complexity of the functionality – that is, those in which users claim that they did not immediately figure out what to click, or that they had to spend too much time to perform a simple operation. Everything else that does not affect the accessibility and simplicity of functionality can be optimized later, in subsequent updates.
The importance of iteration
Since building MVP for startups involves creating a primitive version of a full-scale solution, most likely, you will have to deal with a lot of negative feedback. Some will not like the typography, some will find the navigation inconvenient, and some will not even understand what actions need to be performed to achieve the goal. This is okay. At the same time, those who leave you reviews now are likely to use your solution after its optimization, too – therefore, in order not to lose their loyalty, you should constantly improve it. This will show your audience that you appreciate their opinion and that they also contribute to your project.
Launching Your MVP: Getting It Out There
Each iteration that brings your MVP closer to its finalized version must fulfill a specific business task – this could be confirming or refuting hypotheses, testing functionality, attracting users, choosing the best version from several proposed ones, identifying competitive advantage, etc.
This means that with each new iteration, you may have to take different approaches to each stage of the development cycle, from MVP planning, as well as choosing development tools and startup methodology, to testing and determining methods for collecting user feedback. Ultimately, this flexibility will open up further development prospects for your minimum viable prototype and reduce the risks of its possible failure.
Conclusion
Generally speaking, the benefits of creating an MVP from a business point of view cannot be overestimated. This approach helps reduce the risks of failure, attract investors, ensure a more moderate expenditure of the project budget, evaluate its competitiveness, and much more. In addition, it allows you to quickly enter the market because instead of the time-consuming development, you can spend less time creating its primitive version and, thus, more quickly test its viability and prospects in practice.
If you are just considering the possibility of implementing your business idea in MVP format, feel free to contact us. We will take on all stages of its implementation, from concept approval to usability testing and launch, and will repeat iterations until it transforms into a full-fledged product.
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When you are going to create a new web solution from scratch or optimize an existing one, one of the key indicators of top high quality will most likely be a high response rate (to user actions) and SEO-friendliness.
Unfortunately, client-side rendering, which is done by default in many modern web frameworks and libraries, can become an antagonist for developers pursuing these two goals. In this case, it makes sense to consider the possibility of implementing server-side rendering. Below, we will explain to you what it is, what its features are, with the help of which software tools it can be implemented, and also for which projects it is best suited.
Definition of Server-Side Rendering
Generally speaking, server-side rendering (SSR), as is probably clear from the name, occurs on the backend side. First, the browser sends a request from the client side to the server, after which the SSR server returns an HTML page with all the necessary meta tags, styles, markup, and other attributes. Then, in the browser, the rendering itself happens, the results of which immediately become visible to the end user.
Why is all this necessary if you can use the default option, client-side rendering (CSR)? – you may ask. In fact, everything is simple: search engine crawlers do not recognize the SEO text contained on the pages (or the page, if it is the only one) of the CSR solution. Thus, if the CEO occupies a significant part of the promotion strategy of your project, you can achieve better results only by implementing SSR. Let us add that projects with sophisticated business logic may “suffer” from CSR in the context of performance since the increased load in the form of several synchronous requests will lead to delays in the interface’s response to user actions. And this is exactly the case where server-side rendering can also become a win-win solution.
Currently, SSR technology is actively used in such world-famous solutions as Airbnb, Upwork, YouTube, Netflix, Uber, etc.
What Are the Benefits of Server-Side Rendering?
Now, based on the above, let's look at the key benefits of SSR.
- SEO and social media friendliness. The server side render approach ensures improved SEO ranking through the correct indexing of pages – now, search robots can recognize SEO text and other attributes important for good ranking. First of all, this is due to the fact that now, search robots do not need to read SSR JavaScript code. As for friendliness for social platforms, it is explained by the ability to display colorful previews when sharing SSR-rendered pages – all due to the correct recognition of meta tags.
- Better app/website performance. SSR rendering provides a faster initial page load as the JS to HTML conversion is done on the backend. Thus, users see refreshed content faster than with CSR, in particular when it comes to dynamically updated pages. In the long term, this can ensure a reduced bounce rate for websites and web applications.
- Lower load on the user's device and better user experience (UX). Due to the fact that user requests are now processed on the server side, the user device will experience minimal load. All that remains for it is to interpret the HTML code returned by the server.
What Are the Risks of Server-Side Rendering?
To ensure the objectivity of our review, let's also analyze the disadvantages of server-side rendering.
- Higher TTFB. TTFB or time to the first byte is one of the highest priority indicators of good (or, vice versa, insufficient) performance of web pages. This parameter indicates the time it takes for the browser to receive the first byte of page data processed on the server side. Typically, compared to CSR, the TTFB value is higher because instead of returning a file with links to JS, the server spends some time converting JS to HTML code.
- Limits on the number of requests simultaneously processed on the server side. Due to the increased load on the server, the number of requests processed synchronously will be less than in the case of client-side rendering. Thus, the server throughput will be reduced.
- Need to wait for all the HTML code to load. While the page is loading HTML code under SSR, the user will not be able to perform any new actions on it.
If we add to the above disadvantages a fairly high entry threshold into SSR, as well as an increase in the budget of such projects (due to frequent requests to the server), it becomes clear that this approach is not suitable for everyone.
Server-Side Rendering Frameworks and Tools
As for the server side rendering frameworks and libraries that can be used to process client-side requests on the backend, these include React, Next.js, Nuxt.js, Angular (v7 and newer), and Svelte/Sapper. They use one of the most universal server-side templating languages – JavaScript.
Below we propose to consider server-side rendering React concepts only since React is one of the main tools that we use in web development.
Server-Side Rendering vs Client-Side Rendering
Server-side rendering is not a one-size-fits-all solution since there are situations where its alternative, client-side rendering, is the best choice. In particular, if the content on web pages is updated dynamically – that is, it requires the rendering of some components only (i.e., those with whom the user interacted) while the whole page doesn’t need to be updated, CSR is better suited since part of the content with which the user did not interact will be already loaded.
However, considering that during initial initialization, the content is not displayed until the page is fully loaded into the browser (this can take 2 or 3 seconds, which is critical for a modern consumer of Internet content), when implementing CSR, the site may have poor SEO regardless from the professionalism of SEO specialists (note that this is not a default situation, because with the right approach, lightweight projects with CSR are still ranked well). And this is where the SSR React approach can come to the rescue as usually, React server side components are well-recognized by search crawlers. Thus, by resorting to it, you will be able to ensure enhanced content visibility for search engines.
Server-Side Rendering: SEO vs. Performance
As you can already understand, server-side rendering is capable of providing the best SEO performance for solutions that really need it. In particular, thanks to this approach, search engines will not need to interpret JavaScript. At the same time, if you decide to render in React applying CSR by default, for the React server side rendering implementation, you will have to use additional tools to indicate metadata (for example, React Helmet).
As for performance, in the case of high-load projects, with the server side React rendering, this indicator will be better than with CSR since the SSR website or application will not be limited by the resources of the user device and browser. Also, the user device itself will be less loaded since its only task in the context of updating content will be its output (without rendering).
Conclusion
To sum up, we would like to emphasize that with the correct use of JavaScript frameworks for SSR, you can solve the problem of poor ranking of single-page applications (SPAs) as well as content-heavy websites where SEO and bootstrap performance are critical. On the other hand, CSR is suitable for software with dynamically updated content, that is, content that should change without completely refreshing the page.
However, you should not limit yourself to just these two rendering approaches. In particular, there are also hybrid rendering approaches that combine the best characteristics of SSR and CSR. For example, you can consider the static site generation (SSG) vs SSR couple – perhaps the first option will be the best choice for your project.
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First announced in 2014 by Ethereum co-founder Gavin Wood, today, the concept of the next-generation internet, called Web 3.0, opens up a whole niche for startups. Below, we will look at its basics, describe its advantages and disadvantages, and also find out what technologies can be used to implement Web 3.0 solutions.
What Is Web 3.0?
The Internet that we are used to is defined as Web 2.0. It allows all users to upload content themselves, making it publicly available. This became possible thanks to the emergence of social networks, which over time, instead of providing users with the desired freedom, began to limit them with all sorts of rules and censorship. This, in turn, has become the main reason for looking for new, alternative concepts that would go against these restrictions, giving users more control over their publications.
In this regard, instead of centralized networks, the operation of which was tied to central servers, decentralization was proposed. It had to provide a “smart” distribution of content to servers located throughout the world. Thanks to this approach, widespread availability of user content would be ensured. With this approach, to block specific publications, the consent of all network nodes is needed – instead of just one, as was the case with Web 2.0.
As for technologies capable of implementing a decentralized network architecture, these include, first of all, blockchain, which would transform the centralized Internet into a distributed content database. Actually, this radical transformation would give the world the Web 3.0 Internet.
Today the simplest Web 3.0 formula looks like this: "read + write + own".
Why Is Web 3.0 Important?
Due to its undeniable value for ordinary Internet users, Web 3.0 can be of particular interest to businesses that are constantly developing in the digital plane.
Specifically, by increasing content accessibility, reclaiming ownership of user-created content, and overall end-to-end user centricity, businesses can benefit from launching personalized Web3 websites, apps, and services that aim to increase trust and engagement among their users, as well as providing advertising based on their behavioral patterns.
This way, businesses can strengthen their relationships with consumers and, therefore, increase their profits.
How Web 3.0 Works
As you can already understand from the above, Web 3.0 is based on decentralized networks, but this description is not complete. In particular, Web 3.0 also implies that any Web3 website or application must be able to process information like the human brain, that is, as artificial intelligence and machine learning already do today. This is how an alternative name for the 3rd generation of the Internet has appeared – the semantic web.
This requirement for the “intelligence” of the Internet arose for a reason: since, due to decentralization, users and machines interact with data directly, this data must be recognized by the network not only using predefined algorithms – now, its context has become no less important.
Benefits of Web 3.0
With the right approach, virtually any company that continually grows its online presence can reap a number of benefits from Web 3.0 software development. These include the following:
- Increasing customer loyalty achieved through the AI and smart chatbot introduction aimed at completely personalizing digital content and services;
- Improved analytics thanks to more complete and accurate sets of user data obtained from disparate sources (and, as a result – the ability to create more accurate marketing strategies);
- Automation of a wider range of tasks provided by blockchain, ML, and AI;
- Increased security that only distributed registry technologies can guarantee;
- New partnership opportunities without the involvement of third parties thanks to blockchain and smart contracts;
- Supply chain optimization, also enabled by blockchain that provides full control and transparency of supply chain operations;
- Copyright protection provided by giving users full control over their data (also thanks to blockchain).
Challenges of Web 3.0
Despite the existence of decentralized solutions, it is too early to say that the 3rd-gen Internet already exists. To make this thesis true, developers have to implement connectivity between Web3 solutions so that the data they collect and process become globally accessible.
For example, if we are talking about Web 2.0, in it, data exchange occurs via the HTTP protocol. In this case, there is an intermediary between the participants (namely, the server) on which information, databases, applications, etc. are stored. The concept of Web 3.0 implies the organization of a new level of network interaction, without a server. So far, such technologies do not exist – it can be explained by the limitations of physical equipment and infrastructure in general.
An equally serious challenge is to ensure proper speed of data transfer and processing in the Web 3.0 development solutions. In a more global sense, this means a scalability problem since the need to maintain a proper balance between decentralization and security is most often achieved by limiting throughput, as we can see in the examples of Bitcoin and Ethereum.
At the same time, options to circumvent these obstacles are already being considered – a potential way out of the situation could be the creation of a cross-chain infrastructure to integrate all blockchain networks. Similar solutions (though not so large-scale as to replace the whole Web 2.0) have already been implemented in the Polkadot and Cosmos projects.
Technologies that are powering Web 3.0
Earlier we talked about the need to use AI and ML in Web 3.0, but let's take a look at the full list of technologies that will be relevant for each Web 3.0 developer.
Artificial Intelligence and Machine Learning
Together with machine learning, artificial intelligence in Web 3.0 provides better analysis of user data and creates a personalized user experience based on it. Thanks to this, users get the content they need faster, without getting confused by colossal volumes of useless or only partially useful information. These technologies can also be responsible for automating resource-intensive processes such as data sorting and forecasting. Finally, we should not discount natural language processing – one of the areas of AI that ensures more accurate and context-sensitive recognition of user queries by machines.
Blockchain and other distributed ledger technologies (DLT)
In Web 3.0 application development, blockchain and other DLTs provide better security when storing user data by eliminating centralized control over it. These technologies also make it possible to create tokens (including non-fungible ones, NFTs), which are decentralized digital assets stored on the blockchain. They define ownership of real or virtual objects and, in the future, can be used to protect copyright.
3D graphics and animation
With the faster content delivery typical to Web3, 3D graphics and animation solutions will become commonplace. In particular, Web 3.0 opens up new opportunities for creating realistic three-dimensional objects to ensure an immersive experience that was previously unavailable with any other digital technologies. Supplemented with reality-like animation, these objects can act as avatars of living users and thereby make them full-fledged participants in meta universes.
The future of Web 3.0
Given all of the above, it is unlikely that Web 3.0 will be a single system – we are sure, it will be a comprehensive solution that goes beyond the traditional web. This approach will ensure the management of the Internet by the user community and exclude content monopolization.
As for specific areas of development, the most promising are considered to be meta universes that combine physical, augmented, and virtual realities with their own blockchain-based tokenomics. At the same time, it is important to understand that despite the many points of contact, currently, metaverses and Web 3.0 are different things since those that exist today are still products from centralized IT companies, with their typical problems. Therefore, the solutions that will mark the emergence of Web 3.0 will differ significantly both from the point of view of technical implementation and the very concept of interaction with users as well.
If you, like us, consider the Web 3.0 direction to be promising for your business and already have an idea that will bring this concept closer to reality, you can contact our Web 3.0 development company. We will advise you on the implementation of your project and also select specialists who will guide you from collecting project requirements to its launch.
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If you regularly think about how to optimize your business operations by speeding them up, increasing their accuracy, reducing related expenses, and eliminating risks associated with the human factor, perhaps the introduction of artificial intelligence will be the best option.
Specifically, according to the CompTIA IT Industry Outlook 2024 report, today, about 22% of companies are actively seeking to integrate AI into most of their technological solutions and processes, and 45% of companies are considering its implementation. If you are still in the second category, it's time to figure out which programming language will be able to form the basis of your new highly intelligent software tools.
What Is Artificial Intelligence (AI)?
The term "Artificial intelligence" describes software algorithms and systems that are aimed at solving problems typical to the human mind – such as learning, as well as pattern generation and recognition. Such algorithms are based on colossal amounts of disparate data collected from various sources. Thus, these algorithms form self-learning software solutions capable of analyzing this data and extracting valuable insights from it.
Programming Languages Most Often Used for AI in 2024
It is worth noting that AI-powered solutions may not be based on any software language – this can be explained by the high resource consumption of the AI algorithms that form them, as well as the lack of high-level functions. At the same time, there are seven languages that are most often used in AI programming.
Python
This programming language appeared long before the popularization of AI development. However, thanks to its low entry threshold and extensive compatibility, its community quickly grew, and today, Python is considered one of the three most relevant languages worldwide.
As for the tools for artificial intelligence programming, there are a lot of Python-compatible frameworks, libraries, and APIs, aimed at simplifying and speeding up this process. Among them are TensorFlow, PyTorch, Keras, SciPy, NumPy, and many others. Using them, developers can create high-performance, reliable, and scalable solutions that can solve even the most complex research problems.
R
R, being a statistical programming language, is great for data analysis and visualization. Even though developing artificial intelligence and machine learning solutions is not the primary use case for R, it is still adept at handling very large numbers. So, where popular Python may fall short, particularly in Data Science and Data Analysis solutions, R may be a better alternative.
Additional benefits of this developer tool include support for functional programming, vector computing, and OOP, as well as a number of packages specifically created for AI and ML development (for example, gmodels, RODBC, and OneR).
Java
This portable and scalable programming language is actively used in the development of highly intelligent corporate applications, especially for mobile platforms. In addition to compatibility with popular tools for ML and AI programming, such as the Deep Java Library for deep learning, OpenNLP for natural language processing, and Neuroph for building neural networks, Java is easy to write and debug program code.
It is worth noting that this language is object-oriented and scalable. It also simplifies data visualization and supports Swing and SWT (Standard Widget Toolkit), which allow developers to create attractive and complex graphics and interfaces.
C++
C++ is considered an extremely powerful language for AI programming and can greatly benefit developers when creating games and embedded systems. Like Python, C++ is a mature language, which does not detract from its advantages, such as flexibility and high performance. C++ has several libraries for machine learning and neural networks that help complex algorithms run faster (including MapReduce, mlpack, and MongoDB). In general, many software engineers prefer this language for building projects that require high speed, as it interacts with training modules in a production environment.
Actually, that’s why this low-level language used for AI is primarily a tool for creating complex banking software, cloud systems, and intelligent speech recognition solutions.
JavaScript
JavaScript is a scripting language used to add interactivity to web pages. Even though it is not as popular as the AI programming languages described above, it can be extremely helpful in implementing solutions for Data Science, one of the most promising areas for using JS.
In addition, JavaScript is the most popular programming language in the world, so you won’t have any problems finding the right AI development tools and frameworks that are compatible with it. The popularity of this coding language for AI can be explained by several factors: reliability, stability, abundance of high-level functions, libraries, and tools, as well as fairly low requirements for other technical skills of developers (it is likely that you will not have any difficulty finding dozens of AI tools that support JS, which will cover the whole scope of work related to your AI project) .
Scala
This machine learning language is concise and expressive, and is often used in big data solutions. Scala is a multi-paradigm language specifically designed to express common programming concepts in a simple, convenient, and type-safe manner.
Scala is commonly used in the development of machine learning algorithms and pattern detection in large data sets, and all this – thanks to the built-in Smile data processing library, extensive compatibility with AI frameworks and libraries (in particular, BigDL, Breeze, DeepLearning.scala, and so on), as well as its object-oriented and scalable nature.
Julia
Julia is the best programming language for AI powered scientific solutions and technical projects that require statistical data processing. This is a relatively new language with dynamic typing, parallel programming, and JIT compilation that has proven itself well due to its high speed (Julia-based projects are rarely inferior in performance to their C++-based counterparts), flexibility, and a mature ecosystem.
Many of the tools built into this language use polymorphic dispatch, which makes switching between them much faster than in other languages. It is also worth noting that Julia projects can be integrated with TensorFlow.jl, MLBase.jl, and MXNet.jl.
The Programming Languages That Are Not Recommended for AI
Along with the extensive list of languages for AI development, there are also those that are better used for solving other problems. These are usually niche and low-level languages, such as PHP and Ruby (scripting languages that do not have the needed flexibility and speed to simplify the development process), C (a low-level language that lacks almost all the functions needed in AI development), and Fortran (despite its use for mostly scientific purposes, it has poor functionality).
Ultimately, a seasoned software engineer will be able to cope with any AI development task using any language; another thing is that, given the expected scope of work, the languages that we described in the previous paragraph are much better suited for these tasks.
If you are looking for an experienced team that will launch the digital transformation of your business processes through custom-made AI and ML solutions, feel free to contact us.
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If you are currently looking for a web agency that you can safely entrust with your task regardless of its complexity and scale, this article is for you. Below, we will find out how to identify the best web design agencies and also consider several aspects that will lead you to the best choice.
What Sets Apart Top Web Design Companies
So, what distinctive features should top web development agencies have? In general, you have to check four fundamental ones.
Innovative Design and Cutting-Edge Technology
If we are talking about a top web solutions agency, you should visit and analyze its website – this way, you will be able to understand whether its specialists follow web design trends, use modern technologies, and whether all this is reflected in the design of their website as well. Just check how modern their website looks, and also visit the Blog, Our Services, and Niches We Cover sections – here, you can get a complete picture of how regularly these guys up their skills.
Client-Centric Approach and Custom Solutions
The best web agencies should have a client-focused design approach, and this is always reflected in their values and mission, which can be described either in the same sections of the website or in the more general About Us block. You can also look through their web design portfolio to make sure that the projects they worked on look diverse and do not repeat the same or a couple of good templates.
Case Studies: Success Stories
In general, today, it is difficult to find digital web agencies whose websites do not have a blog with case studies (or a private resource where they are posted and to which you can get access upon request), but exceptions do exist. Ultimately, you are better off avoiding those who fall into the second category because no matter how visually attractive their works are, the benefit of the created UX designs can always be measured by specific metrics. This means that if this analysis was not carried out on any of the previous projects, the same thing could happen to yours, and you will simply get pretty pictures instead of an innovative design that will provide you with the necessary conversion rates, user traffic, etc.
Client Testimonials
Finally, you will need to check reviews about cooperation with web development agencies of your choice, left by real clients. It is better to do this on third-party independent web resources where companies post their short presentations, such as Clutch, Upwork, etc. This way, you will be sure that the insights you received are honest and that you did not just read the praises left by employees of the specific agency about themselves.
Key Considerations When Choosing a Web Design Agency
If, after the research briefly described above, you already have a couple of agencies in mind, you can easily narrow down your choice for one by clarifying the following details.
Setting the Right Budget
If you think that you have already found your ideal web design agency and you truly like its ultimate web designs, make sure that your budget allows cooperation with it. The fact is that the pricing policies of agencies can differ greatly from region to region, as well as depend on their position in the market (experienced ones usually have a higher price tag because of their positive reputation and image).
Performing a Thorough Agency Search
If you had several agencies in mind, you may have filtered out the vast majority (or even all) of them in the previous step. In this case, in order not to be limited to a small sample, you will need to expand your list. To do this, you can use not only Google search results (although this is quite an effective tool for such tasks) but also all kinds of online rating platforms, LinkedIn, and, of course, your personal business connections. It is recommended that, at this stage, you have at least five agencies under consideration.
Asking the Right Questions
Now, it is the time to communicate with representatives of your chosen agencies personally and discuss issues that are critical to your possible cooperation with them. They are typically related to experience in your business niche, experience working on projects of your size, understanding your vision for the financial solution, and the supporting collaboration models and types of services (custom design, redesign, template-based design, etc.) that suit you best.
Conclusion
Now, you know the main criteria by which you can distinguish top web design agencies, and you can safely go in search of such one. And, of course, we cannot miss the opportunity to recommend ourselves to you. In particular, you can clarify the considerations that we provided above with our sales representative to gain confidence that your project will fall into the right hands.
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Perhaps you are one of those people who believe that any experienced software engineer can be involved in any project. But in reality, it doesn’t work like that: depending on your task, you may need different expertise from the core members of your development team. Below, we will highlight existing types of software development and briefly consider their specifics.
Types of Software Development
The division of software development into types primarily depends on the platforms for which the created project is intended, that is, the user environment where it will be deployed. This could be a web browser, cloud, mobile, desktop, IoT, or embedded operating system. There are also platform-independent solutions that can be run on several operating systems without any restrictions.
Ultimately, the deployment environment turns out to be one of the main factors influencing the choice of the project’s technology stack, and, therefore, the developers themselves, who have the appropriate expertise.
Web Development
Web development involves creating different types of software – web applications and websites – that run through an Internet browser. Along with this, you have to understand that to implement your web solution, you will need several specialists at once whose scope of work will be concentrated within the following subtypes of web development.
Frontend Development
Frontend development concerns the creation of that part of the project with which the end user directly interacts. In particular, this consists of creating a user interface as well as functionality that is performed without the participation of a server and database.
Backend Development
Backend development lies in the implementation of the business logic of the project and its connections with the database/databases. This is its server part, which is hidden from the eyes of end users.
Full-Stack Development
Full-stack development involves a combination of frontend and backend development, but unlike them, it requires the participation of more general specialists who are well-versed in both server and browser technologies.
Mobile App Development
Mobile app development is aimed at the implementation of projects for mobile operating systems – usually iOS and Android. At the same time, there are also cross-platform projects that work equally well regardless of what OS is installed on the end user’s device.
iOS App Development
iOS app development involves creating applications completely tailored to work on the iOS operating system. Such projects require developers to have knowledge of Objective-C, Swift, and Java programming languages, as well as platform-native technologies and tools.
Android App Development
Similarly, Android app development is aimed at projects tailored to the specs of the Android mobile OS. To do this, developers need to have strong programming skills in Java and Kotlin, and be able to work with the Android Toolkit.
Cross-Platform App Development
Cross-platform development allows developers to cover several mobile platforms at once. In this case, they create a universal code base based on a single technology stack, regardless of which OS will run on user devices. From a business perspective, cross-platform projects allow you to achieve faster launch and lower budget since instead of several separate applications and teams that will work on them, you can hire just one that will create a software solution that can be simultaneously deployed on numerous platforms.
Embedded Software Development
Embedded software development involves creating solutions to control machines or devices that are more primitive than computers, called embedded systems. This software development model is completely tailored to the specific hardware on which the software solution runs and has significant restrictions on the consumption of its resources.
Desktop Application Development
Desktop application software development consists of creating applications that are used to work offline on user PCs and laptops. Instead of applying the computing power of servers on the hosting provider's side, they rely entirely on the resources of the user device on which they are installed.
DevOps and Continuous Integration/Continuous Deployment (CI/CD)
DevOps is a set of interaction practices between developers, testers, and other IT specialists in a project team needed to increase their performance and improve the quality of the work results. Typically, DevOps is applied to launch new versions of software regularly. In turn, CI/CD is one of the DeOps techniques, which consists of automating the software development process to ensure a recurrent development life cycle with a continuous delivery of the program code.
IoT (Internet of Things) Development
IoT development, also called M2M development, is aimed at creating software for systems where devices exchange data with each other without human intervention. These could be physical security systems, smart home and smart city solutions, logistics systems, and so on.
Cloud Development
Cloud development involves creating software that is run on a remote web server using a subscription-based delivery model. From the point of view of end users, this approach ensures the high availability of such software products since they only need to have access to the Internet.
Augmented Reality (AR) and Virtual Reality (VR) Development
While the development of augmented reality solutions involves using the camera of a smartphone or tablet on the user's device (this is necessary to overlay digital objects in the user's real environment), virtual reality solutions also need the use of special wearable devices, such as VR glasses.
Blockchain Software Development
Blockchain software development involves the creation of decentralized platforms, consensus protocols, smart contracts, and other blockchain-related solutions. Although this type of development became popular thanks to crypto projects, today, it covers a long list of niches, from logistics and healthcare to insurance and finances.
API Development
API development is the creation of software tools that allow independent software components to interact with each other using a set of definitions and protocols. Typically, APIs are used to integrate systems, services, and applications to ensure seamless and secure data exchange between them.
Choosing the Right Development Type
At the very beginning of the article, we already indicated that the deployment environment is the main factor influencing the types of software products that you should focus on creating. However, there are also a number of other aspects that will help you make the correct choice. These may include the following:
- Project needs and objectives – they will help your team to define not only the tech stack but also the most suitable software development methodologies (usually, they are related to Agile)
- Your business niche – it can be finance, healthcare, entertainment, e-commerce, industrial, education, logistics and supply chain, or something else
- The resources you have – the specialists you’ve already hired, the project budget, access to data that will operate your software solution, etc.
As for small projects, they are usually dedicated to web development, mobile development, or desktop development — in such software development types, the talent pool is usually wide, and you will be able to choose specialists with the optimal ratio between expertise and rates. However, don't forget that choosing development services that are too cheap may mean you end up having to redo the project from scratch because it doesn't meet your expectations.
Trends in Software Development
Finally, let's take a brief look at the technologies that will be trending in the coming years and which ultimately can provide a strong competitive advantage to your project:
- Artificial intelligence and machine learning – today, these technologies find a wide variety of applications, from personalized search results and chatbots to smart analytics and forecasting
- Augmented and virtual reality – we have already mentioned these two trends above, so we would like to emphasize that their implementation becomes more and more affordable to project owners
- Internet of Things – we also talked about this trend above; its relevance is explained by the possibility of on-site data collection from devices to which the user does not have physical access
- Personalized user experience – in general, it can be achieved not only with the help of machine learning but also through predefined algorithms
- Blockchain – it’s needless to say that the number of blockchain software development projects is growing every day, and currently, they cover not only the crypto industry
Conclusion
Now, after reading this article, you will be able to understand what type of project you can classify as and what specialists you will need in your project team. At the same time, whichever of the above-described examples of software development you choose, you can always contact us, and we are guaranteed to implement your business idea according to your requirements.

If your website has existed for a long time, this is a reason to think about redesigning it. The fact is that web development trends are constantly changing, and the things that attracted users around five years ago may seem high and dry today.
In particular, several years ago, the independent web resource GoodFirms conducted a survey among designers to find the reasons why users leave their websites. It turns out that about 40% of respondents were sure that this was due to the outdated design. Do you need to look for more explanations as to why you need a redesign? If you don’t, this article is for you.
What Is a Website Redesign?
Website redesign is a modernization that involves changes in the design, content, and functionality of a specific web resource. There may be not only a change in color scheme but also in the website’s structure, which also implies a certain optimization of the HTML code.
Redesign can be done every two years, or less often, every three or four years. However, when the appearance of your website remains the same for five years or more, your users are likely to begin to believe that your business is idle and, therefore, will likely choose a more successful competitor.
Why Is a Site Redesign Important?
Let's imagine that when you launched your website first, it generally satisfied its visitors. However, after a few years, its traffic began to gradually decline, although the quality of your service and/or goods did not decrease. Most likely, the problem is that your website’s design is outdated. Although this may seem to be the only reason why you need a redesign, there are several other reasons that also lead to it:
- You are going to migrate your website to a new engine;
- Despite regularly taking SEO measures, your website is not ranking well in search engines;
- You are planning to expand your audience reach and scale your business;
- Your company has rebranded, and now, this should apply to your website as well;
- You are entering a new market;
- Your product range or the concept of its promotion has completely changed.
Why You Need a Website Redesign Project Plan
In general, there are many goals that you can achieve through a redesign. The benefits of website redesign include improving the user experience, rebranding, increasing reputation, optimizing traffic indicators, conversions, etc., involving the website in marketing campaigns, and so on.
At the same time, whatever goal you pursue, its achievement must be consistent, and each step must be justified from the point of view of business and available resources. Otherwise, you will act chaotically, and the result of these actions will most likely not live up to your desires. To prevent this from happening, you actually need a project plan for website redesign.
How to Redesign a Website: Applying Key Principles for Success
Now, it's time to find out what five sequential phases the correct redesign strategy includes.
Setting Clear Objectives
Any well-thought-out project plan for website redesign implies matching goals and needs to redesign tasks to be completed.
Understanding the Need for Redesign
At the very beginning, you will need to correctly identify the reasons for the redesign. For example, this could be an outdated design, a not-mobile-friendly user experience, the functionality update and complicated website structure related to it, etc. You need to describe all these reasons as precisely as possible to make it easier for your team of designers (and possibly developers) to decide on the scope of work.
Defining Your Goals
Once the reasons are clear, you can define SMART (specific, measurable, achievable, relevant, and time-bound) goals. Special cases of such goals may be increasing traffic, achieving better conversion rates, improving user experience, etc.
Research and Preparation
At this stage, you will have to complete more complex tasks that will lay a solid foundation for your team's further work. They will also help you understand how competitive your website is at the moment and which aspects of it have the highest priority.
Analyzing the Current Website
Your website is probably already connected to some analytics system where you can evaluate the dynamics of its traffic, conversion rates, abandoned carts, and so on. Thus, you have to collect this data, evaluate its changes for better or worse over the last year, and compare these changes with seasonal and local trends in your niche to get the most objective assessment of your website.
Competitor Analysis
You will also have to analyze the websites of your main competitors to understand in what they are good at and what needs optimization. Through this analysis, you will be able to prioritize the tasks that your technical team will have to deal with.
Target Audience Identification
Refine your audience data – this is especially important if you're looking to enter new markets or scale your online business. However, even if your goals are less ambitious, you'll still need to refresh information about your potential customers – their demographics, pain points, goals, needs, etc.
Content Audit
Finally, you should conduct a global content audit – for this, you'll probably need the help of SEO experts. Specifically, if your website's main problem is low search engine rankings, it's likely due to poor-quality content that will need to be optimized or replaced with a new one.
Planning and Strategy Development
Actually, you are left with the last steps before you hand over your website rebuild project to your technical team.
Site Structure and Navigation
Based on the key indicators of your website displayed in the analytics, you will be able to determine which of your website’s navigation elements and structure components need to be changed.
Visual Design Considerations
If your current website seems visually outdated, you will need to identify relevant examples from your competitors and indicate which graphical aspects of their websites you like the most.
Technical Requirements
If you find that your website's performance is suffering or, for example, the website itself is not fully displayed on some mobile devices, optimizing these aspects will require the participation of web developers.
SEO and Content Strategy
If the problem is the poor quality of the content (lack of necessary keywords in the texts, low-quality images, outdated data, etc.), you will need to involve SEO specialists in the project as well.
The Design and Development Process
Now, it’s the practical part of your website redesign roadmap, which requires the involvement of technical specialists and the designers themselves.
Wireframing and Prototyping
Now that the project is in the hands of the designers, they can start creating wireframes according to your requirements for the updated version of the website. As your requirements become more detailed, they will build prototypes based on these wireframes.
Design Mockups
An intermediate stage between the development of wireframes and prototypes can be the creation of mockups. Essentially, these are medium-fidelity sketches of your project that, like wireframes, schematically demonstrate the main components of the website but already have a pre-defined color palette and some graphic objects. Typically, this intermediate stage is necessary for websites with a complex and/or non-trivial structure.
Development and Coding
If your site requires migration to a new CMS or you have discovered problems in the previous stages that can only be solved through changes in its program code, you will have to involve developers to eliminate these bottlenecks.
Testing and Quality Assurance
And, of course, don’t forget to staff your project team with quality assurance specialists who will check if the updated version of your website works correctly before it goes public.
Launch and Post-Launch Strategy
Finally, you can begin preparing for the website relaunch.
Preparing for Launch
If your updated website looks the way you like and all the inconsistencies have been ironed out, it makes sense to check its effectiveness on the representatives of its target audience. This way, you may get additional insights about optimization that can still be implemented before your website’s launch.
Launching the Website
Now, developers can upload a new version of the website to the hosting. It may require you to choose a new hosting provider or a new tariff plan from the old one – this makes sense if you plan to expand the reach of your audience.
Post-Launch Activities
This stage will last exactly until the next redesign. In particular, you will have to monitor the analytics of your update to see whether the new key indicators meet your original business requirements. You will also need to constantly work on your website's SEO by regularly uploading new, relevant content.
Conclusion
We hope that in this article, we have helped you understand how to website revamp, and now, you can begin this procedure as consciously as possible. If you are looking for specialists ready to take on not only the planning task but also the implementation of your redesign project, feel free to contact us, and our team will bring your most ambitious goals to life within your budget and timeline.

What is a SaaS product?
SaaS (Software as a service) is a software distribution model in which a cloud provider hosts applications and makes them available to end users over the Internet. Therefore, SaaS applications are not set up and maintained by companies. A monthly subscription fee gives users access to the ready-to-use software. To make an analogy, the SaaS using process is like renting a vehicle, for which the lessor pays the price and uses it on demand. Nowadays, SaaS presents not as a service but as a necessary element at the center of the functioning of every second business.
Here are some statistics referring to SaaS software:
- The global SaaS market was valued at $237.48 billion in 2022, with projections to reach $908 billion by 2030, growing at a CAGR of 18.7%.
- Over the last seven years, the SaaS industry's size has increased by approximately 500%.
- The U.S. SaaS market is expected to grow at a CAGR of 5.64% from 2023 to 2028, reaching over $186 billion by 2028.
- By 2026, it's anticipated that public cloud spending will constitute over 45% of total enterprise IT expenditure.
- Large companies (with over 1000 employees) use about 150 different SaaS products, comprising 70% of their total software usage.
Top Industries
Leading industries in SaaS adoption include healthcare, financial services, manufacturing, and retail. This trend highlights the importance of cloud-based solutions in driving business efficiency and innovation.
- Manufacturing: Projected to surpass $19 billion in SaaS market value by 2026, with increased adoption of cloud solutions for supply chain, inventory, and production planning driving growth.
- Web and Video Conferencing: Expected to reach $7 billion by 2026, driven by remote work practices and advancements in IoT, AI, and video compression.
- The healthcare SaaS market: Is projected to grow at a CAGR of 19.5% by 2028, driven by ongoing digitalization efforts, including the adoption of electronic health records (EHRs) and telehealth solutions.
- CRM (Customer Relationship Management): Expected to grow at a CAGR of 13.43%, reaching $59.4 billion by 2027, driven by higher adoption among SMEs, cloud-based solutions, and a focus on customer engagement.
- EdTech (Educational Technology): Projected to grow at a CAGR of 19.1% through 2028, spurred by increased demand for virtual learning platforms and educational content.
- HR (Human Resources): Anticipated to expand at a CAGR of 15.8% up to 2028, with growth fueled by the need for efficient management systems, talent acquisition tools, and advanced analytics.
- Property Management: Expected to see a CAGR of 15.5% until 2028, driven by demands for automated rental management and enhanced tenant experiences.
Top Players
To get a clearer idea of what a SaaS product is, here is a list of the biggest SaaS companies known around the world:
- Microsoft Corporation;
- Adobe Inc.;
- Figma;
- HubSpot;
- Trello;
- Zoom;
- Slack.
Suppose you have experience using one of the above products. In that case, you can imagine how it works, why it is convenient, and how important it is to implement such SaaS platforms in your business.
Our company also deals with similar SaaS development services. We implemented the latest technology to build an innovative financial CRM system and booking beauty appointment platform, according to SaaS approach.
Benefits of using SaaS products
So, what are the benefits of this system for you? If you clearly understand what function SaaS products perform and your business purpose, you can formulate precise requirements for the end result of using this service. This section will list the main things that SaaS providers can offer for B2B and B2C businesses.
- You pay only for the resources and functionality that the company actually uses. There is no need to pay for the full range of services that a SaaS provider offers you. You're free to choose the necessary and critical features for your business and pay only for them.
- Economic benefit. This point can be viewed from two angles. First, you know exactly how much you'll have to pay for the subscription period, and you won't have surprises with the increased cost of the resources you've already paid. Second, you won't risk your investment in such a subscription. If your business needs a more powerful or extensive platform to deploy your capacity. You'll end your subscription to one product and switch to another without losing money.
- Accessibility to your team from anywhere. Any device your employees use - PC, laptop, mobile phone, tablet - can use the SaaS product.
- Shared use of the software by the entire team. There is no need to buy a subscription for each user within the same company; the only exception may be the limit of connected users.
- Centralized software updates. There is also no need to worry about updating the paid platform manually; the providers will do everything for the customer.
Business prospects with SaaS products
Enterprises incorporating SaaS products into their business concept are uniquely positioned to benefit from this growing trend. Here are some key business prospects with SaaS products, supported by statistics and numbers:
- Cost savings: SaaS service reduces businesses' need to invest in expensive hardware and software, which leads to cost savings. As a result, companies can save up to 20-30% of their IT costs.
- Scalability: According to 68% of companies, scalability is one of the main benefits of using SaaS. Therefore, a company can quickly increase or decrease its use of software as needed.
- Security: SaaS products offer enterprises advanced security features to reduce the risk of data breaches, including encryption and multifactor authentication. 94% of enterprises report a noticeable increase in security after implementing SaaS.
- Competitive Advantage: 74% of companies claim SaaS gives them an advantage through the quick and cost-effective deployment of innovative software.
Summary
As you have already understood, SaaS products are not only an opportunity to effectively manage business processes and business as a whole but also a practical necessity, without which it will be easy to optimize work processes and implement large-scale projects without a platform for necessary control.
By understanding what working principles SaaS is based on, you can maximize the potential of SaaS in your business and achieve greater success by 2030 and beyond.

Firstly, an interesting fact: there are almost 700 programming languages, but we bet that most developers know and use nearly 15% of the list.
Different programming languages are suited for various projects (mobile and web applications, game development, distributed systems, etc.). Also, it is important to identify the most appropriate language specifically for your project.
In this article, we will look at each of the most popular programming languages according to PYPL and TIOBE rankings in detail — helping beginning developers and entrepreneurs select the right language for starting their digital projects.
Programming Languages Ranking
We tried to find out the most popular programming languages in the year 2024, using official information from PYPL, TIOBE, and GitHub rankings.
- PYPL – The more a language tutorial is searched, the more popular the language is assumed to be. The raw data comes from Google Trends.
- TIOBE – The ratings are based on the number of skilled engineers worldwide, courses, and third-party vendors. Popular search engines are also used to calculate the ratings.
- GitHub – The ratings are created using a yearly review of programming languages’ popularity.
PYPL Ranking 2024
The PYPL (PopularitY of Programming Language) Index is created by analyzing how often language tutorials are searched on Google.
The more a language tutorial is searched, the more popular the language is assumed to be. The raw data comes from Google Trends.
The PYPL index can help you decide which language to study, or which one to use in a new software project.
According to PYPL, 5 most popular programming languages are:

The TIOBE Ranking 2024
The TIOBE (The Importance of Being Earnest) index is an indicator of the popularity of programming languages. The index is updated once a month. The ratings are based on the number of skilled engineers worldwide, courses, and third-party vendors. Popular search engines such as Google, Bing, Yahoo!, Wikipedia, Amazon, YouTube, and Baidu are used to calculate the ratings.
It is important to note that the TIOBE index is not about the best programming language or the language in which most lines of code have been written.
According to TIOBE, 5 most popular programming languages are:

The GitHub Ranking 2024
GitHub is one of the biggest code repositories that boasts a massive developer community spanning across the globe. The repository is also growing at a blazing speed. Nearly 70% of global Fortune 50 companies have lately made contributions to GitHub’s open-source codes.
GitHub also shares a yearly review of programming languages’ popularity. Here are the dynamics of changing the popularity of different languages according to the latest GitHub report:

Top 5 Most Popular Programming Languages in 2024
Understanding programming is crucial for advancing technology across sectors like IT, data analytics, and engineering. As technology evolves, certain programming languages emerge as essential due to their functionality, ease of use, and adaptability.
So, which programming languages will continue to be in demand in 2024 and beyond? We turn to the PYPL index for insights, which ranks languages by learning interest. Here's a quick look at the top 5 according to PYPL, focusing on why they stand out.
1. Python
PYPL rating — 28.59%
- Pros. Python is regarded as the easiest programming language to learn, because of its simple syntax, a large library of standards and toolkits, and integration with other popular programming languages such as C and C++. It is a popular programming language, especially among startups, and therefore Python skills are in high demand.
- Cons. Python’s cons include slower speed than compiled languages, limited concurrency with the GIL, high memory use, and complex debugging due to dynamic typing. It’s also less suited for mobile, embedded, and real-time applications, where efficiency and low latency are critical.
- Common Use Cases. Python excels in AI, data science, and financial sectors, with frameworks like TensorFlow making it a top choice for machine learning. It's behind major platforms like Instagram and Pinterest and powers apps such as Dropbox and Spotify, showcasing its wide applicability from cutting-edge tech to core web services.
2. Java
PYPL rating — 15.79%
- Pros. Java is a classic choice of many backend developers throughout the world and the only official language for Android app development. Java is designed to be a loosely coupled programming language, meaning that an application written in Java can run on any platform that supports Java. As a result, Java is described as the “write once, run anywhere” programming language.
- Cons. Java's downsides include less efficiency in cloud versus server settings and slower performance compared to languages such as C++. It also uses more memory, which can be a drawback in limited-resource situations. Moreover, Java's detailed syntax can result in longer codes, potentially extending development timelines.
- Common Use Cases. Java is widely used for creating business and Android apps, and it supports major websites like LinkedIn, Amazon, and Twitter. It's also used in server applications, handling big data with Hadoop, and web development using JSP and servlets, highlighting its wide-ranging use in software projects
3. Javascript
PYPL rating — 8.7%
- Pros. JavaScript is essential in front-end development for building interactive websites. With Node.js, Javascript can be used to power server-side content, supporting game and communication applications app development in the browser. Javascript has a lot of frameworks that allow stress-free integration with third-party apps.
- Cons. Internet browsers can disable JavaScript code from running, as JavaScript is used to code pop-up ads that in some cases can contain malicious content. Additionally, its dynamic typing system can complicate debugging and maintenance.
- Common Use Cases. JavaScript is used extensively in website and mobile application development. Node.js allows for the development of browser-based applications, which do not require users to download an application. Popular apps built with JavaScript frameworks include Slack, Netflix, GitHub, Facebook, Skype, Uber, LinkedIn, Tidal, and more.
4. C#
PYPL rating — 6.77%
- Pros. C#, developed by Microsoft, is widely used in developing Windows applications, web services, and mobile apps. C# is also known for its strong type system, making code more robust and error-free. Thanks to its object-oriented nature, it's highly preferred for enterprise-level applications. Regular updates from Microsoft ensure it remains relevant and efficient for modern software development.
- Cons. While C# is incredibly powerful for Windows platform development, it's less versatile for programming applications on other operating systems, although .NET Core has made significant strides in cross-platform development. Some critics argue that C# can be less efficient for certain types of low-level programming compared to languages like C or C++.
- Common Use Cases. C# is key for creating desktop, web (via ASP.NET), and mobile applications (using Xamarin), especially for Microsoft products. Popular apps like Visual Studio IDE, games such as "Pokémon Go" and "Monument Valley" developed with Unity, and parts of Microsoft Office showcase C#'s versatility in software development.
5. C\C++
PYPL rating — 6.76%
- Pros. As one of the first programming languages ever developed, C has served as the foundation for writing more modern languages such as Python, Ruby, and PHP. It is also an easy language to debug, test, and maintain. C++ is an extension of C that works well for programming the systems that run applications, as opposed to the applications themselves. C++ also works well for multi-device and multi-platform systems. Over time, programmers have written a large set of libraries and compilers for C++.
- Cons. C/C++ has complex syntax and many features that can make it complicated for new programmers. C++ also does not support run-time checking, which is a method of detecting errors or defects while the software is running. C is not suitable for more modern use cases, such as websites or mobile applications.
- Common Use Cases. C++ has many uses and is the language behind everything from computer games to mathematical simulations. C is often used to program hardware, such as embedded devices in automobiles and medical devices used in healthcare. C/C++ is a basic programming language used for creating most existing operating systems, web browsers, and basic Microsoft products.
How to Choose a Programming Language for a Project?
Choosing the right programming language depends on what you need to achieve with your project. Don't just go by how popular a language is. It's better to ask for advice from developers who have worked on similar projects. They can help you pick a language that fits your project's needs, including how it works, its safety, and how it can grow.
Thinking about which language to use? Feel free to contact us today to make a smart choice for your project's future.
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The HealthTech inductry is developing rapidly: according to Statista, by the end of 2024, its global capitalization is expected to reach a record 610.20 billion US dollars. This growth is driven by increasing demand for advanced healthcare solutions, especially as the number of digital offerings in this sector rises. With this growth comes intensified competition, pushing organizations to focus on building user loyalty by enhancing the quality of their services. In the healthcare context, providing a top-tier user experience (UX) becomes essential for driving user satisfaction and engagement. This article delves into the principles, challenges, and best practices for crafting exceptional UX in MedTech, telemedicine, and digital health solutions.
HealthTech Market Overview
One of the largest segments of the medtech market is medical equipment, which is projected to reach $511.20 billion in capitalization by 2024. Key areas of development include:
- Diagnostics and intervention: Innovative tools for early detection and treatment of diseases.
- Genetic research: Advanced solutions to decode and leverage genetic data.
- Patient mobility: Technologies that improve access and convenience for patients, especially those with chronic conditions.
This evolution is largely influenced by an aging global population, which drives sustained investment in healthcare technology. To remain competitive, medtech companies must integrate cutting-edge systems and focus on wearables, telemedicine, and personalized healthcare UX design to deliver unparalleled user experiences.
The Role of Telemedicine in Healthcare UX
Telemedicine has transformed healthcare delivery by enabling remote consultations, diagnosis, and treatment through digital platforms. Its success depends heavily on intuitive UX design, ensuring that both patients and healthcare providers can interact seamlessly.
Key UX Considerations for Telemedicine:
- Real-Time Accessibility: Patients and doctors must connect effortlessly through video calls, chats, and data-sharing interfaces, regardless of their device or location.
- Intuitive Navigation: Complex interfaces can delay care. Clear layouts and straightforward workflows are essential for urgent medical situations.
- Security and Compliance: Telemedicine platforms must protect sensitive health data, adhering to HIPAA, GDPR, and other regulatory standards.
- Integration with EHR/EMR Systems: To provide seamless care, telemedicine solutions must integrate with electronic health records, ensuring real-time access to patient histories and reports.
- User Support: Telemedicine systems should include built-in assistance features, such as chatbots or FAQs, to guide users through the platform.
In turn, a well-thought-out medical UX design can speed up the execution of targeted actions by users, minimize the risk of errors, and generally reduce the cognitive load that new users of a particular digital solution face the first time.
Digital Health and Personalized Care
Digital health encompasses a broad range of solutions, including fitness apps, chronic disease management platforms, and AI-driven diagnostic tools. Personalization is at the heart of digital health, enabling tailored care for individual patients.
Key Elements of Personalization in Digital Health UX:
- Adaptive Dashboards: Dashboards that adjust to display metrics relevant to specific users, such as glucose levels for diabetics or activity levels for fitness enthusiasts.
- AI-Powered Recommendations: Leveraging wearable data and patient history to provide personalized health insights, such as medication reminders or lifestyle adjustments.
- Behavioral Nudges: Notifications and reminders based on real-time data from wearables, such as prompts to stay active or alerts for irregular heart rates.
- Collaborative Tools: Features that allow patients to share health progress with their healthcare providers, enabling more informed decision-making.
- Data Visualization: Simplified visuals, such as graphs and heat maps, to help patients understand complex health data without requiring medical expertise.
Integration with Wearables
Wearable devices are enabling real-time data collection and fostering proactive patient care. These devices, including fitness trackers, smartwatches, and specialized medical wearables, provide essential metrics such as heart rate, blood pressure, sleep patterns, and oxygen levels.
To stay relevant in the modern healthcare ecosystem, medtech systems must:
- Seamlessly integrate with wearables: Facilitate data synchronization from devices to centralized healthcare systems.
- Enable flexibility: Support compatibility with various devices to cater to diverse patient needs.
- Enhance real-time insights: Convert wearable data into actionable metrics that healthcare providers and patients can use to make informed decisions.
Integration with wearables empowers healthcare providers to:
- Monitor patients remotely, reducing hospital visits.
- Leverage AI-powered analytics to predict health deterioration.
- Tailor personalized care plans based on real-time patient data.
What Is HealthTech UX Design?
Healthcare UX design focuses on creating digital healthcare solutions that are functional, visually appealing, and accessible to all users, including patients and medical staff. A well-executed healthcare UX design reduces cognitive load, minimizes errors, and speeds up workflows in stressful environments.
“When designing for the Healthcare industry, it is crucial to keep in mind that every solution you create affects your users’ health – therefore, you cannot afford to produce half-baked or generic solutions as it puts someone’s well-being at risk. Cater to your users, make your design accessible, and ensure that your solutions are consistent and flexible across all mediums – that’s how you create a truly excellent and literally life-changing product”
Ivan Hohanov, Head of UX
Providing a premium user experience should be one of the fundamental goals in any business sector. However, when it comes to the provision of medical services, often the achievement of this goal is the only possible option to provide some patients with a specific service, which can be explained either by temporary restrictions in mobility or by the presence of permanent mental or physical disabilities. This actually causes the need to create digital solutions according to the principles of simplicity, intuitiveness, and ergonomics.
It is noteworthy that medical personnel are no less in need of advanced user experience in healthcare software products, as they are often forced to act urgently in stressful situations and follow error-free decisions.
Key Principles of HealthTech UX Design
Let's look at a few fundamental principles underlying effective UX design for healthcare:
- Accessibility: patients should be able to fully use the functionality of a particular digital solution, regardless of their physical and mental disabilities.
- Conciseness: the user interface should not be overloaded – instead, it should demonstrate only those functions that the user currently needs.
- Mobility: users must be able to access at least some of the services provided by a particular healthcare organization remotely.
- Consistency: the functionality of a specific digital solution must be presented consistently and logically.
- Control: user actions within a specific digital solution must be controlled to prevent errors.
- Context: the interface of digital solutions must be context-sensitive so that users can intuitively perform targeted actions in it.
Best Practices in HealthTech UX Design
In this paragraph, we suggest that you consider a number of best practices that will help you bring HealthTech UX design to life.
Focus on the end user
Before you start working on a design, you will need to try to perceive it from the point of view of the end user to understand what possible problems they may encounter and what solutions will be optimal for them. Design thinking methods such as user research, as well as creating user personas and user flows based on surveys, personal data, etc., can help you with this.
Don't overload your screens
You should not place all the functions that have to be presented in your digital solution on the same screen. Instead, try to create a convenient, context-sensitive hierarchy and, according to it, divide the functionality into groups, placing each of them on a separate screen.
Create intuitive navigation
Your users must understand intuitively how to perform this or that action. Typically, the “rule of three” is used for this – that is, to complete a particular task, the user must complete no more than three steps. If this is not possible, make sure that your product contains clear and unambiguous hints leading to the goal.
Maintain balance
The visual component of your product also plays an important role: in particular, the user interface should look well-balanced, harmonious, and have a consistent style without being annoying.
Ensure compliance with data security standards and regulations
Make sure that while using your product, consumers cannot accidentally leak personal data (that is, every operation requiring their personal data must be performed by them consciously, after obtaining their consent). To do this, you will need to focus your design development process on FDA recommendations, HIPAA, GDPR, and ISO 62366.
Provide alternative control and navigation tools
Your users may have certain limitations in using the vast majority of digital solutions, so your main task will be to help them overcome them within your product. In particular, we are talking about ensuring product usability and accessibility by providing alternative navigation and control tools (for example, through voice input). More information on how to achieve accessibility in interaction design can be found in the WCAG 2.0 guidelines.
Consider implementing responsive design
If you consider launching your solution on multiple platforms (for example, on mobile and desktop devices), you will need to implement a responsive medical app design that will scale the screens of this solution to the dimensions and orientation of a specific user device.
Base on user feedback
As you complete the prototyping stage and/or launch new versions of your ready-made solution, you need to collect feedback from real users and optimize the UX design in accordance with their complaints, needs, goals, and wishes.
Challenges Of UX Design For HealthTech
Along with following the principles described above, you should also understand what challenges you will have to overcome during the UX design implementation.
Bringing complex workflows into the digital plane
Many workflows in the healthcare sector are multi-step and require the participation of multiple parties. In this regard, one of the most difficult tasks of UX designers is to transfer them to the digital plane, accompanied by simplification and reducing the risk of errors. As for overcoming this challenge, most often, teams have to start their work on a project by creating its tree-like architecture - this is the easiest way to remove unnecessary steps and correctly group functionality that requires the same actions on the part of the end user.
Ensuring regulatory compliance
When designing a user interface, designers must take into account standards that ensure the protection of private user data and prevent its abuse. The same applies to providing accessibility for solutions that patients with disabilities can use. After work on the project is completed, it will need to obtain a certificate of conformity from an independent authority authorized to issue such certificates.
Data visualization
If a particular digital solution operates on large volumes of data and generates analytical conclusions based on them, UX designers may well encounter difficulties in presenting them in a simple and understandable form for the end user. Usually, this problem is solved by testing several visualization options: charts, line graphs, pie charts, etc., and choosing the one that seemed most convenient for the vast majority of respondents.
Final Thoughts
We hope that now, you understand the differences between the process of developing a UX design for a medical sector and the usual one. That’s why it’s so important when looking for a UX design healthcare contractor to turn to specialists who already have experience creating digital products in this niche. In particular, you can contact us, and we will bring your idea to life in accordance with all standards and regulations accepted in your region.
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