
InfraTech in Essen brings together what is rarely found in one place within the infrastructure sector: municipalities, construction companies, engineering firms, and technology providers. From January 13 to 15, 2026, the focus was on civil engineering, road construction, supply and disposal, public space design, and mobility.
Michael Banf and Max Becker were there for Perelyn. Not with an exhibition booth, but with a question: Where can AI make a tangible difference in infrastructure planning and execution?
The infrastructure sector faces challenges that cannot be solved by individual technologies alone – climate adaptation, ageing networks, rising demands for efficiency and sustainability. At the same time, digitalisation and data-driven approaches are creating new opportunities to optimise planning processes and make decisions on a more informed basis.
What we took away from the conversations at InfraTech: the interest in AI across the sector is real. What is often missing is not ideas, but clear pathways from idea to implementation. That is precisely where we come in.
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The proceedings from the "AI in Production" workshop at KI2025 have been published. Among the contributions is a paper by our team on the use of the Model Context Protocol (MCP) in industrial production environments.
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Dominik Filipiak and Michael Banf are co-authors of a community paper on the 2025 Topological Deep Learning Challenge, published in the Proceedings of Machine Learning Research. Their contributions feed into TopoBench, an open benchmarking library for the research community.