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    Definition

    Retrieval-Augmented Generation (RAG)

    RAG is a method where an LLM retrieves information from external sources (documents, databases, web) before generating a response, improving relevance and quality.

    Why Retrieval-Augmented Generation (RAG) Matters

    In RAG-style systems, being present in retrievable sources (and being easy to match semantically) can strongly affect whether you're included in AI answers.

    Key Factors

    Your content's presence in retrievable sources, semantic clarity, and topical coverage all affect RAG-based retrieval.

    Action Steps

    Publish authoritative pages that "answer the question." Make your brand/entity easy to match (consistent naming). Build topical clusters that cover your category comprehensively. We test whether your brand is retrievable across AI engines.