The problem
Staff couldn't find anything in a decade of accumulated internal documentation. Keyword search returned either nothing or four hundred results, so people asked colleagues instead — which is expensive.
What I built
Chunked and embedded the corpus, added hybrid keyword-plus-vector retrieval so exact terms like part numbers still work, and constrained the model to answer only from retrieved passages with inline citations. Built a small eval harness of real staff questions to catch retrieval regressions before deploy.
The outcome
Answers arrive in under a second with links to the source document. Because every answer is cited, people trust it enough to actually use it — and when it's wrong, they can see why.
Need something like this?
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