--- language: en title: "RAG" description: "RAG combines information retrieval and response generation. Learn why current sources can be used in AI searches and what limitations remain." canonical: "https://tropk.ai/en/resources/glossary/rag" last_modified: "2026-10-12T16:15:06.917Z" --- # RAG Reviewed on 2026-10-06. ## What it means RAG stands for [Retrieval](/en/resources/glossary/information-retrieval)-Augmented Generation. It is an approach in which a system searches a database or index and uses the retrieved material as context to generate a response. Retrieval can take place on the web, in internal documents, or in another collection. RAG describes the approach, not a single implementation. ## Why it matters for marketing For marketing, the implication is that a response can use information published after the model was trained. This makes access to sources, their quality, and how up to date they are relevant. It also explains why correcting a page is different from trying to change a model’s internal knowledge. The team controls what it publishes; it does not fully control retrieval and generation. ## Example in practice A company updates its documentation to explain a newly launched integration. If a search system retrieves this document, it can use the new information in its response without the model being trained again. If it retrieves an old comparison, however, the response may remain out of date. The result depends on the material found and how it was interpreted. ## How to apply or verify When investigating an incorrect description, check the available sources and the sources actually displayed. Verify public access, links, [indexing](/en/resources/glossary/indexing) where applicable, and clarity of conditions. Publish corrections with evidence and monitor new responses. For private databases, include document reviews, permissions, and retrieval tests; this scenario involves different responsibilities from public brand discovery. ## Important distinctions RAG does not prevent hallucinations or guarantee that the most recent source will be selected. It also does not mean that every response from every assistant consulted the web. A system can respond without retrieving documents. In your analysis, identify the mode and the evidence observed instead of attributing an exact architecture to a response based on text style alone. ## Sources and references - [Optimizing your website for generative AI features on Google Search]() — Google Search Central - [The AI Search Glossary: A definition of 300+ terms]() — Profound ## Continue a leitura - [AI search]() - [Grounding]() - [Indexing]() ## About the author [Vinicius Pacheco]() Responsible for Tropk’s technical content, focusing on crawling, indexing, structured data, and agent access to content. --- [All pages in Markdown]()