Solutions using Machine learning and Artificial Intelligence

For some time now, work on the use of artificial intelligence and machine learning algorithms have entered a new phase, after years of research and analysis, it has become a stable solution with a real impact on processes. Implementation of ML and AI allows not only to automate simple processes and reduce the need for human effort, but today’s implementations also change increasingly difficult areas and processes.

Advantages OF ML

pełne dopasowanie effectiveness

Algorithms are becoming more and more effective, with a sufficiently large batch database, the solution can be trained to achieve very high efficiency.

zwiększone szanse performance

Applications and systems work without interruption, do not get sick, have no holidays – they work for your success at all times.

łatwe wdrożenie reliability

Like all solutions in the area of digitalization, ML and AI are characterized by much lower failure rates and problems than the previous way of implementing business processes.

WHAT IS MOST IMPORTANT TO US?

1/

Customer’s needs

Understanding the needs of our clients as well as their current and future goals.

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Recognition

Understanding the specifics of the business, business model and organizational structure.

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Management

The highest quality project management methodology

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Smooth implementation

Open and fast communication processes at every stage of the programming work.

Technologies

We always optimally select tools so that your needs and goals are met 100%. In order to create dedicated web applications, we use the following technologies: AWS, Kubernetes, Docker, GraphQL, Rest API, PWA, Python, PHP, TS, Symfony, React.js, Angular.

aws
kubernetes
docker
graphql
rest
pwa
python
php
typescript
symfony
react
angular
 

Case Studies

DA VINCI MEDICA

DA VINCI MEDICA

Da Vinci Medica is an internal project of Da Vinci Studio, whose aim was to create an automatic system for the analysis of public bids, price changes and the emergence of trends. The system focuses on the analysis of data on public procurement related to health care.
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