The use of artificial intelligence and machine learning to
improve the quality of life and productivity of employees.


To improve employee efficiency and productivity.


Using AI to make recommendations for employers and employees.


Measuring 200 factors affecting human life quality.


Workwell is a cloud-based application that allows you to measure 200 factors influencing the quality of human life. Thanks to the use of a series of academic studies translated into artificial intelligence and machine learning algorithms, it formulates recommendations for employers and employees that can improve the productivity, efficiency and financial results of each company.

  • Scope

    UI, Frontend & Backend Development, Cloud Solutions

  • Industry

    Business, Productivity Management

  • Region / Country:

    United Kingdom


Hundreds of factors affect our quality of life, many of them scientifically analyzed and it has been proven that changes in levels of physical activity, diet, alcohol and nicotine consumption, housing and work-related stress levels make us more or less happy and fulfilled. Praxis Workwell Ltd, a British research and development company that developed the concept of the application, decided to check how these factors affect our productivity at work.


For this purpose, a survey with 200 questions was created and it was conducted on a group of 5,000 respondents. The answers in statistical form served as a knowledge base for artificial intelligence and machine learning algorithms, which on their basis make specific recommendations for the employee and the employer.

The scikit learn library was used to build a reliable and efficient ML model.

The back-end of the application was developed in .NET technology, while for the front-end we used React.

Due to the well-thought-out design of the UX, it takes only 15 minutes to answer the 200 questionnaire-related questions.

Project result
Project results

Thanks to the Workwell application, employers can now check what factors affect the quality of life of employees on the basis of anonymous surveys.

Using artificial intelligence and machine learning algorithms, the application makes recommendations for changes that may translate into improved quality of life and productivity.

The tool also suggests what employers can change to improve the overall satisfaction of their employees.

Data from the application can contribute to the improvement of the efficiency of any company, because satisfied and relaxed employees are sick less often and are more productive, which translates into financial results.

In the second phase, the project was carried out for a UK government organization and COVID-19 questions were added to the algorithms to understand how the pandemic affects workers’ well-being and what support can be given to them to stay productive.