Fayrix
About Fayrix
Fayrix provides world-class custom & offshore software development. Relying on 14 years of experience and a talented team of 1500+ developers, we are ready to execute software development projects of any scale. We provide to our clients flexible terms, competitive rates & different models of partnership - time & materials, dedicated teams or project-based full outsourcing.
Guarantees and transparency. We work in full compliance with the highest international legal & financial standards. Availability. With 10 R&D centers in key educational and technology hubs of Russia and CIS, Fayrix has a direct access to the top IT talents. We are ready to provide at least 3 devel...Read more
Fayrix provides world-class custom & offshore software development. Relying on 14 years of experience and a talented team of 1500+ developers, we are ready to execute software development projects of any scale. We provide to our clients flexible terms, competitive rates & different models of partnership - time & materials, dedicated teams or project-based full outsourcing.
Guarantees and transparency. We work in full compliance with the highest international legal & financial standards. Availability. With 10 R&D centers in key educational and technology hubs of Russia and CIS, Fayrix has a direct access to the top IT talents. We are ready to provide at least 3 developer CVs for each position in 3 business days.
Flexibility. We can allocate a full-time dedicated team with temporary relocation to our clients, work under Time & Material approach or develop custom projects with fixed deadline, price and a detailed tech specs.
Dedication. Fayrix works under a documented methodology, elaborated in 12 years of our experience, with weekly project progress reports, regular calls and discussions with our clients.
Key Insights
Services & Focus
Industry Focus
Client Focus
Portfolio
Predicting Search Results Relevancy for Home Depot
Building a Machine Learning model to increase the relevancy of search results to a search query entered by a user.
The result: 15% more accurate search results.
Warehouse Optimisation based on Machine Learning for S7 Airlines
Inventory optimization system to collect and analyze data, create forecast models of the repair and supply divisions of S7 Engineering Department.
Machine Learning Model for Medical catheters
Building a Machine Learning model trained with a set of 3 566 763 unipolar and bipolar ECG signals to predict ECG strong activation points within a particular selected windows of interest.
The result: Over 96% of predicted activations were located within ± 1 ms from actual activation in ECG.
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Location
97293740180