Healthcare platform


To create a modern software solution that would facilitate efficient mental healthcare

Our Client

GazeHealth is a technology company that provides healthcare facilities, mental health providers in particular, with a modern analytics platform helping them make efficient data-driven decisions and deliver better patient outcomes.


6 Full-stack Developers, 2 AI Data Scientists



Services Provided

Software Development Outsourcing

Tech Stack

Front-end: React, TypeScript, Redux + Redux-Saga, Material UI, styled-components, React Router, Formik + Yup, Storybook, D3, DevExpress, React-vis

Back-end: NestJS, TypeScript, TypeORM, PostgreSQL, RxJS, Faker, AWS Cognito



Since 2019


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About the Project

GazeHealth is a healthcare platform that consists of two parts - an EMR system and an analytics tool. They can be used together or separately. The EMR system lets to collect, visualize and manage data about patients. The analytics tool lets mental health specialists track and study case records of different patient groups.

Our Engagement

Our experts were engaged in the development of both parts of the GazeHealth platform.

Using the best software development practices our developers built the EMR system consisting of four key parts:

  • Patient profiles that contain all patient data including doctors’ notes, test results, prescribed treatment courses, attached files, etc.;
  • Online doctor appointment booking page;
  • Page with recommendations for patients on mental health improvement and data about the last events (e.g. test results, prescribed medicines, etc.);
  • Provided by the GazeHealth analytics tool Sankey Chart that demonstrates the most relevant case records and treatment courses based on Big Data and AI.

Being empowered by advanced technologies like AI and Big Data we also developed the analytics tool. Using it, doctors can create patient groups based on age, gender, etc., and then choose points of interest in different sections - symptoms, screenings, diagnosis, treatments, and outcomes. Based on the choices made the tool provides a Sankey Chart and a number of additional charts. All in all, we have implemented about 15 charts that visualize one or another aspect of patients’ case records. Still, the key feature of this tool that we have built is its ability to provide the most suitable variants of treatment based on AI and Big Data

In the course of working on the project, our team successfully addresses several challenges


  • To efficiently visualize case records of a patient group based on the aspects of special interest.
  • To implement the key feature of the GazeHealth solution - finding the most suitable and efficient treatment method for each case based on Big Data and AI.
  • To implement treatment process tracking that would cover crises in the course of disease and treatment as well as consumed medicines.
  • To provide routing based on a user role and a user company.



It was decided to use Sankey Chart covering all the functionalities that we had to implement. As long as none of the available solutions covered all over needs we built this functionality from scratch using D3. As a result, we have developed the Sankey Chart where a user can click on the needed sections and form the needed flow. All other additional charts are represented on the ground of the chosen flow.


Our data scientists have implemented the tool’s ability to offer the best treatment by harnessing the power of AI and Big Data. Alternative ways of treatment are demonstrated in the mentioned above Sankey Charts and a table containing figures and percentages that explain why a particular alternative treatment variant is better than the one that a user has chosen.


To implement treatment tracking in the best possible way, our developers decided to build a custom chart that would combine a time lime chart for medicine intake tracking and a line chart for test result demonstration. Consequently, they have built somewhat a mix of a calendar and the two mentioned charts that perfectly represents medicine intake and test result changes in the course of treatment. The crises are also demonstrated there.


To provide routing based on a user role and a user company, we used AWS Cognito. With its help, we created different user groups. Additionally, we have implemented integration with our database that stores data on companies partnering with GazeHealth. The react-router v6 has been used to create routing in a way that pages to which users do not have access even are not added to the routing object. As a result, the GazeHealth solution has very flexible and easy-to-maintain routing completely based on a company and a user role.

Client Success

GazeHealth is a provider of a successful healthcare platform that is used today by numerous healthcare facilities. With its help, mental health specialists deliver better care and treatment while patients receive a better experience and treatment outcomes.

Due to the high professionalism of our team, an advanced, robust, and secure healthcare solution with very helpful features have been delivered. This is a solution that is easy to use and maintain. It brings benefits to both businesses and users.

Czech Republic

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