Start with classification​

Most enterprise AI is limited or high risk. The obligations differ sharply:

Classify every system early. A use case that looks harmless can land in high risk the moment it touches employment or creditworthiness.

Build the controls in, not on​

The Act rewards teams that designed for it: technical documentation, audit logs, and human-oversight controls are far cheaper to build during development than to retrofit under a deadline.

This is exactly what our Data & Compliance practice does — map each system to a tier and a concrete checklist before it becomes a launch blocker.

Not legal advice — we deliver the technical controls; pair us with your counsel for binding interpretation.

The demo-to-production gap​

Most RAG prototypes skip the three things that decide whether the system survives contact with real users:

1. Evaluation. Without a golden dataset and regression tests, every prompt tweak is a gamble. We gate deploys on faithfulness and citation accuracy.
2. Access control. Retrieval must respect who is allowed to see what. Bolting this on later means re-architecting the index.
3. Monitoring. Hallucination rate, latency, and cost drift over time. You want alerts, not customer complaints.

How we approach it​

At nicojahn we ship every RAG engagement with an eval harness from day one and deploy into the client's own EU cloud region. The model is provider-flexible; the quality bar is not.

See our LLM & GenAI services or get in touch.