Pure LLM pipelines impress in demos and fail in compliance. The model is good at proposing. It is unreliable at guaranteeing the same inputs produce the same document. When a wrong field is liability, you need a different architecture.
The pattern that works: a deterministic core (templates, schemas, validation) plus an intelligence layer that proposes values and flags gaps, plus a human who accepts or rejects before anything is final.
What to measure
Documents per week before vs after. Time per packet. Rework rate. Reviewer accept rate. If you cannot measure those, you cannot tell whether the AI is saving time or creating new cleanup work.
Related
Document Intelligence on the site is this pattern in a stealth engagement. AI Pilot Rescue is the sprint when you already have a stalled pilot and need a production path with an ROI target.