We were at Hannover Messe 2026, and across many conversations it quickly became clear: you can’t think of industrial AI like a generic chatbot. In engineering and production, AI has to do more than give good answers. It has to run reliably, make its decisions traceable, and fit the real conditions on site.<\/p>\n
On the shop floor, even small inaccuracies can lead to safety risks, process issues or high costs. That’s why industrial AI has to be built and evaluated differently from consumer applications. For us, the focus was mainly on explainable AI with traceable decision paths, plus context-aware search across technical documentation and operational data, sovereign deployment models for sensitive environments, and systems that consider latency, safety and data protection from the start.<\/p>\n
The conversations in Hannover confirmed what’s been taking shape for a while: industrial AI isn’t just about bigger models. It’s about solutions that work within the rules and responsibilities of real engineering and production systems. That’s where the experiment ends and the solution that actually helps in daily work begins.<\/p>\n","protected":false},"excerpt":{"rendered":"
We were at Hannover Messe 2026, and across many conversations it quickly became clear: you can’t think of industrial AI like a generic chatbot. In engineering and production, AI has …<\/p>\n","protected":false},"author":21,"featured_media":12305,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","footnotes":""},"categories":[1,24],"class_list":["post-12303","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-allgemein","category-events"],"acf":[],"yoast_head":"\n