Data
Grounding
Grounding is the practice of constraining an AI model's output to verifiable sources — typically by requiring it to cite specific documents, database rows, or tool results. Grounding is the most reliable defense against hallucinations.
Related terms
- RAG (Retrieval-Augmented Generation) — RAG is a pattern in which an AI model retrieves relevant documents from a knowledge base at query time and uses them as additional context to generate its response.
- Hallucination — A hallucination is when an AI model generates text that is fluent, confident, and factually wrong.