Enterprise RAG System for Legal Firm — 10x Faster Contract Research

The firm maintained 50,000+ documents — contracts, judgements, client briefs, regulatory filings — across 15 years of practice. Junior lawyers spent 3–6 hours per case on research and precedent finding. Senior partners had no reliable way to query institutional knowledge. Contracts were being drafted without consistent cross-reference to prior firm work.

XPndAI built a private, air-gapped RAG (Retrieval-Augmented Generation) system deployed on the firm's own AWS environment:

• ▸Document Ingestion Pipeline — PDF, DOCX, and scanned document processing with OCR; structured chunking by document type (contract clause, judgement paragraph, regulatory section)
• ▸Private Vector Database — all embeddings stored on-premise; zero data leaves the firm's AWS environment
• ▸Semantic + Keyword Hybrid Search — combines meaning-based retrieval with exact-term matching for legal precision
• ▸Matter-Scoped Queries — lawyers can restrict searches to a specific client matter, practice area, or date range
• ▸Citation Tracing — every AI answer includes exact source document, page, and paragraph — no hallucination risk for legal use