Retrieval-augmented generation over the contracts, manuals, policies and records your team already searches by hand.
RAG is a pattern where the system searches your own documents first and then answers using only what it found, citing the source — instead of answering from a model's general training.
The practical consequence is that answers are checkable. Every response points back to the passage it came from, so someone can verify it rather than trusting it. For contracts, policies and compliance material, that difference is the whole value.
Because a general assistant has never seen your documents, and will produce a confident answer anyway.
A general model does not know your contract terms, your internal policy, or last year's procedure. Asked anyway, it will still answer. RAG constrains the system to material you supplied, and makes the source visible so a wrong answer is obvious rather than plausible.
Retrieval respects the access rules you already have, so people see answers drawn only from documents they were already allowed to read.
Document search is one of the easiest places to accidentally widen access. Permissions are part of the retrieval design rather than a filter applied afterwards.
Thirty minutes on a call is usually enough to tell whether this is the right shape for it.