Uncover hidden energy savings potential in your buildings portfolio.
Proactively monitor your buildings to detect inefficiencies and optimize electricity use with real-time data and insights.
Use our AI-powered BEI platform to uncover hidden inefficiencies and drive energy savings across your buildings.
Enhance analytics with our SkySpark plugins and deliver deeper insights to optimize energy performance.
Integrate our AI-powered solutions to enhance your data analytics solution.
Check out our case studies showcasing the possible practical benefits of using machine learning for HVAC operation and energy data analysis. Find and fully exploit the full potential for energy savings.
Our objective is to improve energy efficiency through state-of-the-art tools and algorithms. We have over 10 years of experience with mathematical modeling of energy consumption and various HVAC appliances.
Perspectives Large language models (LLMs) have rapidly become one of the hottest topics across industries, and the building and energy domains are no exception. Over
In the realm of energy data evaluation, machine learning models have unlocked significant potential. These tools support everything from energy conservation analysis to anomaly detection
Some years ago, there was an energy-saving modernization project on a building in the Czech Republic. Manual HVAC controls were replaced by a modern automation
As electric vehicles (EVs) become more common, managing their charging demand presents new challenges – especially in buildings with limited grid connections. In this week’s
Energy Twin and the University Centre for Energy Efficient Buildings (UCEEB) of Czech Technical University in Prague explored the rising importance of load-side flexibility in today’s dynamic energy systems.
Energy savings are a cornerstone of any robust ESG strategy, driving both environmental responsibility and financial performance. At Energy Twin, we leverage advanced AI to
