A technique where AI systems retrieve relevant documents or passages from the web (or a database) before generating a response, rather than relying solely on information in their training data. RAG allows AI assistants to provide current, sourced, and cite-able answers. From an SEO perspective, RAG systems need to find and rank your content highly in order to retrieve and cite it — making relevance, content organization, and topical depth critical. Most modern AI assistants use retrieval-based approaches, making traditional ranking-like signals (authority, clarity, comprehensiveness) as important to AI search as they are to Google.
Part of the Plain Intelligence glossary. See all terms.