Retrieval-Augmented Generation (RAG)

Retrieval-augmented generation (RAG) is the method behind AI search answers that cite sources: rather than relying only on what a model memorized during training, the system first retrieves relevant documents from the live web or a database, then generates an answer grounded in them. ChatGPT search, Perplexity and Google AI Overviews all use a form of RAG.

For brands, RAG is why being crawlable and clearly written matters again: if your page is retrieved, its facts can shape — and get cited in — the answer. Content that states claims plainly and backs them with data is easier for a RAG system to lift accurately.