We develop predictive and analytical models to plan energy production, storage and consumption by interpreting complex data and integrating machine learning and artificial intelligence.
We support the energy transition, new development models and relationship with the local area, the use of renewable sources and distributed generation through improved performance and interoperability between different energy production systems.
Environmental sustainability and new models of development and relationship with the local area also involve the control and implementation of performance.
We offer the most advanced digital tools to efficiently simulate and manage local renewable energy production and its sharing among individuals, businesses, local authorities and the third sector.
From initial configuration and economic evaluation to operational energy and administrative management. From algorithms for distributing the economic incentive to the app to promote more conscious consumption habits.
Energy monitoring of buildings, management of energy consumption in production and retail facilities, control and efficiency of cogeneration plants. We help companies plan based on consumption forecasts and the analysis of peaks and troughs to make energy supply flexible and efficient.
The right amount of energy, only when needed, at the service of comfort and production processes.
Automation and digitisation of infrastructures, processing and interpretation of IoT data in real time. These are the keys to detecting and avoiding disruptions and blockages in advance.
Machine learning and artificial intelligence allow monitoring the health of production facilities and power grids to maximise performance, improve maintenance planning, and optimise investments and operating costs.