AI solutions for empowering your business
Purpose built solutions tailored to your needs, allowing you to focus on other tasks worry-free.
Purpose built solutions tailored to your needs, allowing you to focus on other tasks worry-free.
Everything you need to know about us
Founded in Prague at the beginning of 2021, Euler Technologies has been the forefront of pioneering technologies, specializing in artificial intelligence, machine learning, data analytics, software development, and advanced algorithm design. We are committed to exceeding our clients' expectations by delivering unparalleled quality in every project.
Our expertise spans across critical sectors:
Our mission
At Euler Technologies, we strive to create unique and scalable software solutions utilizing cutting-edge technologies, customized to the needs of our clients.
What we stand for
Selected projects
Predicting GHG emissions using machine learning
Under the new CSRD directive and ESRS standards, large corporations and select SMEs must report their own greenhouse gas emissions as well as Scope 3 emissions from their value chain. To determine Scope 3 emissions, companies can use proxy variables and models based on cross-sectional data analysis, rather than collecting data directly from their value chain entities.
Our unique model captures spatial trends in emissions and utilizes satellite imaging and data mining to predict emissions of industrial plants using publicly available information, significantly improving prediction accuracy over using emission factors, and allowing for simpler estimation of emissions for a larger number of subjects in the value chain.
Algorithm for reassessing commercial real estate prices
Innovative statistical model for commercial property valuation, addresses a crucial gap in the housing market valuation, particularly for appraisal offices and large investors in need of a reliable index tool for property monitoring and reevaluation.
The model's novelty lies in its approach to indexing individual property characteristics across two successive terms, providing a nuanced analysis of market dynamics. Our model will also be featured in the Acta Monaca scientific magazine, in the fall 2024 issue.
Neural networks for predicting spot and derivatives prices in financial markets
Implementing state-of-the-art ML algorithms inspired by winning submissions of the M Competition for forecasting methods including neural networks for predicting future moves in financial markets allows us to create versatile models which periodically and automatically adapt to current market trends. This allows our arsenal of algorithms to outperform benchmark returns at lower or equivalent risk.
The integration of machine learning in financial markets is not just about predictive analytics but also about understanding market sentiment, optimizing portfolio management, and automating trading activities.
