How can we make the energy transition for millions of homes faster, more affordable and better informed? That was the central question behind the Energie-AIdvies project Spotr and Sobolt took on one year ago.
To answer this question, Spotr developed an AI platform that automates a large part of the building inspection and energy advice process. Instead of relying on time-consuming manual surveys, Spotr automatically creates a digital building profile using aerial imagery, street-level imagery, interior photos and public datasets. AI then translates this information into building condition assessments, maintenance recommendations and retrofit scenarios.
As part of the project, Spotr developed a fully automated inspection pipeline, integrated energy and maintenance data into a Single Asset View, and created AI-driven maintenance recommendations and scenario planning tools that help housing associations evaluate different investment strategies. The result is an integrated platform that enables housing associations to understand the condition of their assets faster and make better-informed decisions about when and where to invest in maintenance and retrofit. The technology is already being used by housing associations in the Netherlands and the United Kingdom and forms an important foundation for the next generation of AI-supported asset management.
Read more about how you can implement AI in your asset management processes in the whitepaper The essential AI-stack for housing associations
The Energie-AIdvies project was co-funded by the European Union through the European Regional Development Fund (EFRO) under the Kansen voor West III programme. This support enabled Spotr and Sobolt to accelerate the development, validation and commercial deployment of the AI technology.
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