Glossary
Retrieval-augmented generation (RAG)
Also called RAG.
Definition
Retrieval-augmented generation is a pattern where a system first searches your own content for passages relevant to a question, then gives them to a language model to write an answer based on those sources.
Why it matters when you’re buying
RAG is the usual way to make AI answers reflect company knowledge without retraining a model. Retrieval quality, how permissions are enforced and whether answers cite their sources decide whether people can trust it.
How it relates to other terms
The search step usually compares embeddings stored in a vector database, and a large language model writes the final answer.
Where to go next
- AI & ML Platforms: news, companies and community questions
- How to evaluate AI & ML Platforms vendors: criteria, questions to ask and red flags
- RAG and vector search: the latest stories and threads on this topic
Written by Techarda editors · Updated . Think a definition is wrong or missing something? Email engage@techarda.com. All terms.