Machine Learning
Development and testing
Our experts developed and tested machine learning algorithms to improve geolocation and positioning accuracy. Thanks to the symbiosis of technologies, our programmers were able to develop a suitable solution and successfully test the prototype from the second month of cooperation. Magenta Favorita's experienced staff quickly integrated the algorithms into Baseflant's existing software.
Evaluation and refinement
After successful testing, there were repeated but immediate refinements. Each refinement was followed by repeated, thorough testing and evaluation of the new features. After short iterations, the Magenta Favorita developers made all the necessary adjustments and refinements to optimise performance and accuracy.
Our experts developed and tested machine learning algorithms to improve geolocation and positioning accuracy. Thanks to the symbiosis of technologies, our programmers were able to develop a suitable solution and successfully test the prototype from the second month of cooperation. Magenta Favorita's experienced staff quickly integrated the algorithms into Baseflant's existing software.
Evaluation and refinement
After successful testing, there were repeated but immediate refinements. Each refinement was followed by repeated, thorough testing and evaluation of the new features. After short iterations, the Magenta Favorita developers made all the necessary adjustments and refinements to optimise performance and accuracy.
An interesting case of collaboration with Baseflant. Baseflant is a start-up that develops software for navigation systems. The client is constantly striving to improve the accuracy and efficiency of geolocation, often refining existing solutions. They turned to Magenta Favorita to help them design and implement machine learning algorithms to improve their product.
Analysis and planning
We carried out an in-depth analysis of Baseflant's needs and current software issues.
Magenta Favorita's experts identified key areas for the application of machine learning and geolocation optimisation. From the very first stage of cooperation, the client was surprised by the professionalism of our staff and wanted to add another project immediately. However, the Magenta Favorita team is focused on quality, not quantity. Therefore, we were forced to finish what we started.
Analysis and planning
We carried out an in-depth analysis of Baseflant's needs and current software issues.
Magenta Favorita's experts identified key areas for the application of machine learning and geolocation optimisation. From the very first stage of cooperation, the client was surprised by the professionalism of our staff and wanted to add another project immediately. However, the Magenta Favorita team is focused on quality, not quantity. Therefore, we were forced to finish what we started.
Achieving results
By implementing machine learning algorithms, Baseflant was able to significantly improve the location accuracy of its devices.
Improved accuracy of navigation algorithms by 30%.
Reduced data processing time by 25%.
Increased software user satisfaction by 20%.
Unfortunately, due to confidentiality, we are unable to disclose details and everything described is agreed with the client in advance. The improved system has allowed us to enter new markets and use the product in unexpected areas. New features developed through machine learning have helped Baseflant improve the efficiency of navigation systems and attract new customers.
Working with Magenta Favorita has helped Baseflant to significantly improve its products and increase its competitiveness in the market. The Magenta team is happy to contribute to the success of the start-up and immediately took on the new project. We look forward to further fruitful cooperation.
By implementing machine learning algorithms, Baseflant was able to significantly improve the location accuracy of its devices.
Improved accuracy of navigation algorithms by 30%.
Reduced data processing time by 25%.
Increased software user satisfaction by 20%.
Unfortunately, due to confidentiality, we are unable to disclose details and everything described is agreed with the client in advance. The improved system has allowed us to enter new markets and use the product in unexpected areas. New features developed through machine learning have helped Baseflant improve the efficiency of navigation systems and attract new customers.
Working with Magenta Favorita has helped Baseflant to significantly improve its products and increase its competitiveness in the market. The Magenta team is happy to contribute to the success of the start-up and immediately took on the new project. We look forward to further fruitful cooperation.
Other company cases