"Rodopski Izvor" str. 60, 1618 Manastirski Livadi, Sofia, Bulgaria
+359 888 805 727


Incorporating ML and AI leads to increased efficiency, reduced costs, improved safety, and enhanced sustainability, making them indispensable tools for modern energy, transport, and construction projects.


We are also an unique partner in R&D projects, able to provide an engineering testground and scientific perspective, built on data and advanced algorithms and approach.

Construction sector AI&ML

  • Design Optimization: AI can assist in the design phase by optimizing structural designs, reducing material waste, and improving cost efficiency.
  • Project Scheduling: Machine learning can create accurate project schedules, taking into account various factors like weather, resource availability, and historical data, which helps prevent delays.
  • Quality Control: AI-based image recognition systems can inspect construction materials and structures for defects, ensuring higher quality and safety standards.
  • Risk Assessment: AI models analyze project risks, helping construction companies make informed decisions about budgeting and resource allocation.
  • Safety Monitoring: AI-powered cameras and sensors can monitor construction sites for potential safety hazards, alerting supervisors in real-time to prevent accidents.
  • Energy sector AI&ML

  • Grid Management: Machine learning helps utilities manage energy grids more efficiently by predicting demand, optimizing energy distribution, and reducing losses.
  • Predictive Maintenance: AI algorithms predict when equipment in power plants or renewable energy installations needs maintenance, reducing downtime and operational costs.
  • Energy Consumption Forecasting: AI models analyze historical data to forecast energy consumption patterns, helping utilities plan for peak demand periods and optimize energy generation.
  • Renewable Energy Integration: AI is used to forecast renewable energy generation from sources like wind and solar, enabling better grid integration and energy storage management.
  • Energy Efficiency: Machine learning can optimize building energy systems by adjusting lighting, heating, and cooling based on real-time occupancy and weather data, reducing energy consumption.
  • Transport sector AI&ML

  • Traffic Management and Optimization: AI-powered traffic management systems use real-time data from sensors, cameras, and GPS to optimize traffic flow, reduce congestion, and minimize travel times.
  • Autonomous Vehicles: Machine learning algorithms enable self-driving cars and autonomous public transportation systems by allowing vehicles to perceive their environment and make real-time decisions.
  • Predictive Maintenance: AI can predict maintenance needs for vehicles and infrastructure, helping to prevent breakdowns and improve the reliability of transportation services.
  • Route Planning: AI algorithms help individuals and logistics companies find the most efficient routes for transportation, reducing fuel consumption and emissions. Public Transportation Optimization: AI is used to optimize public transportation schedules, ensuring that buses and trains arrive at the right time and place to maximize passenger convenience.