evidence-based-rag

To ensure traceability in legal compliance retrieval, use evidence-first RAG to extract verifiable evidence units from a knowledge base. It enforces design invariants for non-assumption and entity binding, preventing the generation of unsubstantiated claims with direct source citations.

Yes, RAG can detect conflicting claims during due diligence by retrieving information from a knowledge base and identifying contradictory statements across documents. It surfaces these conflicts and provides explicit confidence and risk signals for each finding.

Evidence-based retrieval evaluates answer sufficiency by extracting verifiable evidence units, checking subject existence through hard gates, and applying entity binding. It outputs explicit confidence and risk signals to ensure conclusions are directly supported by source citations.

The best way to perform auditable information retrieval for risk assessment is using evidence-first RAG. It enforces traceability and non-assumption invariants, ensuring all conclusions are directly supported by source citations rather than generated assumptions.

Yes, this retrieval approach enforces data integrity through hard gates for subject existence and entity binding. These design invariants ensure that extracted evidence strictly adheres to the specified knowledge base and correctly attributes obligations to the right entities.

You need conflict detection in compliance document analysis when reviewing multiple legal agreements for a specific entity. It flags contradictory statements across documents, ensuring your risk assessment is based on solid, verified evidence rather than conflicting claims.