RAG / GraphRAG

Grounding AI answers in retrieved evidence

RAG (Retrieval-Augmented Generation) is a pattern where an LLM retrieves relevant documents as evidence before generating an answer. GraphRAG adds a knowledge graph (entities and relations), so retrieval runs over a relational structure rather than isolated document chunks. It reduces hallucination and makes answers traceable.