RAG Knowledge Assistant Saves 500+ Analyst Hours a Month at a Financial Firm

We built a retrieval-augmented (RAG) assistant that answers questions directly from the firm's approved documents — policies, filings, and internal research — and attaches the exact source passages behind every answer, so analysts can verify and audit each response. Because the data was sensitive, the entire system was designed to keep information inside the firm's own environment, with role-based access controls so users only retrieve documents they are permitted to see. No client or regulatory data was used to train any third-party model. Key elements of the build: - Retrieval over the firm's approved document library, with citations on every answer - Role-based access controls enforced at retrieval time - A deployment architecture that keeps sensitive data inside the firm's environment - An evaluation set of real analyst questions to measure and monitor answer accuracy Because RAG answers from live documents, updates are instant: when a policy changes, the assistant reflects it immediately with no retraining. Analysts went from hunting through folders to asking a question and getting a sourced, trustworthy answer in seconds.