Concept
aka retrieval-augmented generation

RAG

Pattern where a model is grounded on retrieved documents fetched at inference time.

Definition

Retrieval-augmented generation pairs a language model with a search step: a query is embedded, top-k documents are retrieved from a vector database, and the model conditions its answer on them. RAG reduces hallucinations, enables fresh knowledge without retraining, and supports source citations.

Common use cases

  • Enterprise search
  • Customer support
  • Documentation Q&A

Related terms

    RAG — AI Glossary | Railwail