Delivering Trustworthy Legal Precedents with Agentic RAG

Our customer, a global legal research platform, serving law firms worldwide, was fairing poorly on efficiency of the attorneys using the platform. Attorneys spent 18–20 hours per case matter, determining which precedents were truly authoritative. We delivered an AI-powered citation ranking system that evaluates judicial hierarchy, binding status, and subsequent treatment by higher courts. Integrating data from Westlaw, Bloomberg Law, and their AWS DynamoDB repository, the system ranks results by jurisdictional relevance and flags overturned rulings. By embedding agentic RAG with Pinecone vector search, the platform now delivers prioritized, trustworthy case lists to associates. As a result, research time has been cut nearly in half— to just 8–10 hours per case. We are still working to improve efficiency.