Markets

Driver for progress

The world is changing. The population is growing and the climate is becoming more changeable. Innovative measures are needed. Greenhouse gas emissions must be reduced by at least 55% by 2030. Apply smart technology together and create accelerated sustainability.



Livable cities

Livable cities

Smart green cities

To support the quality of life in urban areas, we are applying new technical solutions. These solutions make buildings more efficient, air quality better and the city as a whole more livable. To apply these solutions effectively, collaboration is a must. We are driven to deliver the best eco-insights for effective climate adaptation.

Better AI

Artificial intelligence, or AI, enables computers to do the work of multiple human brains in a fraction of the time. At Sobolt, we use AI concepts such as pattern recognition to develop smarter solutions to sustainability problems. As a result, our technology contributes to autonomous decision-making, enabling companies, municipalities and individuals to make informed choices about the future.

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Sustainable impact

By investing in a green energy system, we can ensure a sustainable future for our children. But, even if the COP-26 climate agreement is adhered to, there is a realistic chance that global warming will continue. Raising this awareness is of great importance.

Improved solar planning

The energy transition requires a new way of thinking. Energy production is shifting from centralized to decentralized and traditional ideas of energy distribution are no longer applicable. The sun only shines during the day and the wind does not always blow. Our energy needs no longer match energy production at all times. It is clear that energy storage is rapidly becoming of great importance. The solution lies in smart applications that connect all elements of the grid. More solar energy?

Energy & buildings

The energy transition requires profound innovation. To simplify the transition for homeowners, we have created the artificial thermographer. Using a deep-learning algorithm, we are able to generate individual insulation reports for a large number of thermographic images/homes. This creates awareness among residents - crucial to achieving an effective energy transition.