Description:
Applications of reliability theory include the assessment of system and equipment reliability, failure analysis, and forecasting. Technological failures and operator errors are assessed to help improve safety and optimize operational processes.

Description:
We develop AI-based business decision support systems that integrate data, deliver predictive insights, automate decisions, and enable real-time performance monitoring.

Description:
Advanced ECG analysis based on algebraic relationships between ECG intervals, supporting early disease diagnostics, clinical decision support, and development of health technology solutions.

Description:
Probabilistic modeling of meteorological extremes, climate change impacts, and rare events is performed using advanced statistical analysis, extreme value theory, and data integration methods.

Description:
Risk and uncertainty analysis helps assess system security, model sensitivity, and data uncertainty. This service allows you to identify risk scenarios, reduce their likelihood, and make effective, data-driven decisions.

Description:
We deliver market, revenue, and price forecasts, financial and investment risk analysis, and future scenario modelling to support evidence-based business decisions under uncertainty.

Description:
AI, data analytics, and data science services, including task automation, predictive modeling, natural language processing, computer vision, recommendation systems, big data analysis, optimization, risk and fraud detection, and the creation of customized solutions, are provided.

Description:
Smart information integration tools are being developed and applied for the synthesis of data from different sources, the aggregation of expert knowledge, and the automated modeling of information flows.

Description:
Analysis of the uncertainty and sensitivity of modeling results helps to assess the accuracy of models, identify parameters that influence results, and define the limits of forecast reliability for more accurate risk assessment and better decision-making.

Description:
Failure and longevity data are analyzed, and system reliability, uncertainty, and sensitivity of results are evaluated. This helps identify risk factors, predict failures more accurately, and optimize maintenance and operational decisions.

Description:
AI-based solutions for fault and defect detection and predictive monitoring, enabling reduced downtime, early anomaly detection, and improved reliability of technological processes.

Description:
Advanced time series analysis, forecasting, and segmentation for identifying trends, predicting process behaviour, and supporting data-driven decision-making in business.

Description:
We develop AI-based economic and financial models for forecasting, risk management, and decision automation, enabling companies to use data effectively and improve business performance.

Description:
We optimize logistics, manufacturing, and other business processes using mathematical and data-driven models to reduce costs, allocate resources efficiently, and support informed decision-making.

Description:
Optimisation of energy storage battery parameters for prosumers, increasing self-consumption, reducing energy costs, and improving return on investment.