Compliance turnaround cut from months to minutes for a safety-critical manufacturer
The Situation
A German manufacturer of safety-critical rail systems ran certification and compliance workflows the way they had been run for decades: engineers manually cross-referencing product specifications against regulation and against the historical record of previous certifications.
Each pass took weeks to months. The people doing it were senior engineers whose time was the most expensive in the building, spent on document work instead of engineering.
Why it was hard
Safety-critical means zero tolerance for a wrong answer. A generic chatbot summarizing regulations is a liability, not a tool.
Every output needed a traceable evidence path: which specification clause, which regulation, which precedent. If a human auditor asks why, the system has to show its work.
What Was Built
An agentic pipeline that reads three sources together: the product specification, the applicable regulation, and the certification history.
A supervisor-worker architecture keeps each agent scoped to one job, with every conclusion tied to its source documents. The output is not an answer, it is an answer with its evidence attached.
Engineers review and approve. The system does the months of reading; the human does the minutes of judgment.
The Results
What This Means For You
If a regulator reads your outputs, AI is an evidence problem before it is a technology problem, and getting it wrong is a liability, not a bug. The audit tells you whether your data, governance, and controls can support AI a regulator will accept, before you build it.
Not sure where you stand? Take the free AI Readiness Calculator →