What is Retrieval-Augmented Generation (RAG)?
Last updated 2026-06-19
Retrieval-Augmented Generation (RAG) is a technique where an AI retrieves relevant documents at answer time and uses them to ground its response. It is why up-to-date, well-structured content can shift what an assistant says about you.
Why RAG is good news for GEO
If a model only used training data, you would be stuck with whatever it learned months ago. RAG means the assistant can pull in current pages. Publish clear facts, get cited by trusted sources, and you can influence the answer now rather than waiting for the next training run.
How to win in a RAG world
- Keep your key facts current and easy to find
- Earn mentions on sources models retrieve from
- Use structured data so passages are easy to lift
- Offer a clean machine-readable version of your content