Appsilon | R Shiny | Machine Learning
visit site- $10,000+
- 50 - 249 employees
- Warszawa, Poland
Appsilon Data Science is a data science company founded in 2013 and located in Warsaw, Poland. The team of fewer than 50 employees serves mostly enterprises in the IT, business services, health care and medical, and retail industries. Their services include custom software development, BI, big data and consulting, SI, and AI
Client Insights
Industry Expertise
80%
10%
5%
5%
Client Size Distribution
Midmarket ($10M - $1B) 10%
Enterprise (>$1B) 90%
Common Project Size
$50K-$199K 9 projects
$10K-$49K 8 projects
<$10K 6 projects
Clients
This provider has not added their key clients.
Highlights from Recent Projects
The first project was a UI/UX design for a pharmaceutical company. The goal was to create a user-friendly digital ecosystem across 5 markets in APAC. Appsilon | R Shiny | Machine Learning delivered the UX/UI prototype design in Figma, resulting in an on-time delivery of the prototype design. The client was impressed with the quick and positive responses to their needs, and there were no areas for improvement identified.
The second project was a software development project for a chemicals & biotechnology company. The company was looking to create four enterprise dashboards to visualize research data. The project was completed successfully, with good and flexible communication, well-documented code, and a good working relationship. The client was impressed with Appsilon | R Shiny | Machine Learning's commitment to finding solutions to fit their needs.
The third project involved UI/UX design and custom software development for a medical center. The goal was to develop an R Shiny application to combine clinical outcomes with place-based data and enable users to build custom, dynamic logistic regression models. Appsilon | R Shiny | Machine Learning was able to deliver all of the project goals on time and demonstrated unique expertise with R Shiny. The client was impressed with the team's understanding of their goals and the ability to make strategic and novel improvements to the project. No areas for improvement were identified.
Timeliness
Service Excellence
Value
Would Recommend
Awards
2023
2023
2022
2022
2022