We are Data Scientists and Machine Learning Engineers who are passionate about leveraging our skills and expertise to help innovative startups with solving complex AI problems. We collect and clean data, test and train models, and help you with integration.
We provide high-quality help with your company’s data operations, development, and our support lasts for as long as needed, which is proven by our many long-term partnerships.
We always keep an eye on emerging technologies, algorithms, and frameworks that help up deliver state-of-art custom solutions. Our tech stack is varied, and it helps us accommodate your current infrastructure.
We are experts in Deep Learning and its applications in various domains including Computer Vision and NLP.
We retrieve trends, patterns, and predictions from your data that offer valuable insights on revenue growth and cost reduction opportunities.
We create data pipelines and backends and help you integrate trained models in production to deliver end-to-end solutions to business problems.
We develop scalable and stable solutions to serve millions of potential users.
Research & Publications
Originally BroutonLab was established by the alumni of the Institute of Mathematics, Mechanics and Computer Science, SFedU. It’s famous for its outstanding schools of Mechanics (founded by Vorovich Iosif Israilevich) and Algebra (founded by Simonenko Igor Borisovich).
Besides having years of experience with commercial development for startups and companies, we also keep close to our academic roots with scientific research regular publications in respectable journals. We enjoy this, as it helps to keep us creative and involved in technological progression.
Experts in research and industry
With constant research, development, and working on custom solutions, there’s always something going on at BroutonLab. Our effort is widely recognized, and we do our best to promote data science, data-driven operations, and fractional hiring. Here is what’s going on at our company:
Intel Delta Course “High-performance computations, optimisation and applications”
Anna Berger has presented her final project “Performance comparison of SVM and DNN in image classification” implemented using Intel tools for machine learning and optimisation (DAAL). The school took place in Nizhniy Novgorod, Russia and was devoted to High Performance Computing, Machine Learning and Computer Vision.
We review the books on RL/DL.
Michael Yurushkin took part as technical reviewer of “Deep Reinforcement Learning Hands-on” book.
Award of Excellence
Michael Yurushkin has been recognized as a Distinguished Participant at the Microsoft Summer on Concurrency held in Saint Petersburg, Russia, in collaboration with ITMO National Research University