Work · Case study
Document review thatcites its own sources.
01 / Challenge
Analysts were reading the same clauses in every new document set. What mattered lived in thousands of pages nobody had time to re-read, and anything the team did surface had to be traced back by hand before it could be relied on.
02 / Approach
We grounded a language model in the client's own document store. Retrieval runs against permissioned indexes, every answer carries the passages it was drawn from, and an evaluation harness scores each release against a fixed question set before it ships.
Nothing is answered from the model's memory alone. Where retrieval confidence drops, the workbench says so and hands the question to a reviewer rather than guessing.
03 / Outcome
Faster first pass
Answers with citations
Analysts open a document set and ask it questions instead of reading it front to back. Every answer arrives with its citations attached, so the checking that used to follow the search now happens inside it.