Solutions
AI innovations
Development and adaptation of AI solutions for industrial and energy tasks
- Examples:
- Creating computer vision models for analyzing equipment defects (cracks, corrosion) based on data from cameras or drones
- Development of predictive algorithms for forecasting the wear of key equipment
- Tools for voice control of reporting and access to technical documentation
- Feature: Use of open frameworks (TensorFlow, PyTorch) with adaptation to industry specifics (for example, training models on data from thermal cameras or vibration sensors)
Open ecosystem
Creation and support of an ecosystem based on open source software
- Examples:
- Development of plugins for Open-Source platforms (Apache Kafka, Kubernetes) for industrial analytics tasks
- Participation in communities (LF Energy, ROS Industrial) for the integration of AI solutions into open standards (OPC UA, MQTT)
- Development of proprietary libraries (for example, for processing data from sensors in power grids)
- Feature: interoperability - ensuring compatibility of solutions with different systems (SCADA, ERP) through APIs and open-source drivers
Integration
Integration of AI systems into existing infrastructure
- Examples:
- Implementation of AI modules in legacy management systems (for example, integration of predictive analytics in Siemens SIMATIC)
- Configuration of hybrid cloud solutions (AWS Outposts, Azure Stack) for data processing on edge devices (drones, sensors)
- Development of middleware for data synchronization between AI platforms and industrial equipment (for example, connecting AI algorithms with PLC controllers)
- Feature: Consideration of cybersecurity requirements (using open-source tools like Suricata to protect industrial networks)
" AI doesn’t replace people — it frees their time for innovation: automation of routine inspections increased labor productivity by 35%, and open platforms made this accessible to everyone "
" Open ecosystems and AI are a synergy where software flexibility multiplies deployment speed: we reduced integration time by 60%, while reliability doubled "
" AI turns failures into predictable events: our predictive analytics reduced downtime by 40%, while open-source algorithms provide the freedom to tailor solutions to any challenge "
Based on real experience
Our team have many years of experience in implementing digital solutions
