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Retrieval and RAG

What is Retriever?

The component that finds candidate documents or passages

A retriever searches an index, the web or a vector database for information related to the query. Its output feeds later reranking and generation stages.

What Retriever means in GEO

In a RAG pipeline, publishing is not enough. A page must be discoverable, enter the candidate set and survive reranking.

Why it matters

Make titles, entities, passages and internal links accurately express the questions for which the page is relevant.

What to check in practice

Identify the stage where the source disappears: access, initial retrieval, reranking, generator context or citation selection.

How it connects to other concepts

Retriever belongs to retrieval and rag. It is best analyzed alongside related terms because AI visibility depends on several stages and signals rather than one isolated optimization.

Common mistake

Blaming final copy when the document never reached the model that writes the answer.

Turn these concepts into metrics

Bee LLM tracks mentions, citations, position, sentiment and competitors across major AI engines.

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