GEO & AI Search

RAG (Retrieval Augmented Generation)

Retrieval Augmented Generation is a method where an AI model retrieves relevant external documents at query time and uses them to ground its generated answer, rather than relying only on its training data.

It is why fresh, well-structured, publicly accessible content can appear in AI answers even if the model was trained before that content existed. For example, an assistant answering a current question may fetch and cite live web pages. Being retrievable and quotable is the entire game.