Insights from day-to-day engineering
What AI actually does in engineering design today, how EU data privacy works in practice, and what engineering teams can learn from each other.
ChatGPT for internal documents: secure and GDPR-compliant?
Many teams want to point ChatGPT at their own files. What risks this creates, when the use is GDPR-compliant, and how a dedicated solution differs from the public chatbot.
AI for technical documentation that cites its sources
How an AI backs every answer about your technical documents with a source: the exact file and page. Verifiable, auditable, no unnoticed hallucinations.
3 Questions Every New Engineer Asks. And No One Can Answer Quickly.
New engineers ask the same three questions every day. The knowledge exists but cannot be retrieved. How KoAssist solves the onboarding problem.
Multimodal AI: Why Images Matter as Much as Text in Engineering
Technical drawings, calculations, screenshots from CAD systems: engineering knowledge is largely visual. Why AI systems that only understand text fall short in mechanical engineering.
The Biggest AI Advantage in Mechanical Engineering Is Already on Your Servers
Mechanical engineering companies in the DACH region sit on a data treasure the rest of the world does not have. Why almost no one uses it, and how AI changes that.
What AI Actually Delivers for Engineering Teams Today
AI assistants promise a lot. What of that really works in everyday engineering, and where the limits have to be drawn honestly.
EU Hosting and AI: What It Really Means for Engineering Data
Engineering data is often highly sensitive. What EU hosting actually guarantees for AI systems, and which questions procurement teams should be asking.