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A GraphRAG backend for legal document analysis — clause extraction, cross-document reasoning, and grounded answers over contracts, statutes and case law — used by 1,000+ lawyers in production.
Lawyers reviewing contracts and case bundles need to find specific clauses, compare them across documents, and trace how a statute applies to a fact pattern.
Pure vector RAG could find similar text, but could not reason about relationships ("which clauses in this contract conflict with §4 of that statute?"). Off-the-shelf legal-tech products produced answers without traceable citations — unusable in practice.
A GraphRAG backend that builds a knowledge graph over each document set — clauses, parties, defined terms, references — and combines graph traversal with dense retrieval.
Answers cite specific clauses and the path through the graph that produced them, so the lawyer can verify the reasoning in seconds.
Ingestion extracts structure from legal documents (clauses, defined terms, cross-references, parties) and stores them as both vector chunks and graph nodes.
Query routing decides whether a question is "find" (vector) or "compare/relate" (graph traversal) or both.
A grounded LLM synthesises the answer with mandatory citations to clause-level anchors. Multi-tenant isolation is enforced at every layer.
