Technical Term
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RAG
AI and RAGRAG is a system that retrieves information before generating an answer. Instead of answering only from model memory, it searches for relevant fragments and uses them as context.
What means RAG
RAG: RAG refers to a system that retrieves information before generating an answer. In an AISEO review, it helps AI systems find useful fragments, understand context and reuse information without inventing or mixing signals.
AISEO Area: AI and RAG. This tag helps to place the term within the glossary and understand if it belongs to crawling, semantics, performance, security, AI, accessibility or certification.
It matters because answer quality depends heavily on what is retrieved. If the website does not provide clear fragments, the system may choose poorly or not choose you at all.
- Split content into clear, self-contained blocks.
- Add enough context for each fragment to make sense on its own.
- Connect entities, sources and trust signals where appropriate.
- Remove decorative text that does not add useful information.
Common errors
Creating text blocks that depend too heavily on previous context.
Mixing different concepts in the same section without hierarchy.
Not providing enough signals for AI to identify source, entity or intent.
Treating RAG as a minor detail instead of a signal within the system.
Frequently asked questions about RAG
What is RAG?
RAG refers to a system that retrieves information before generating an answer. In an AISEO review, it helps AI systems find useful fragments, understand context and reuse information without inventing or mixing signals.
Why should RAG be reviewed?
It matters because answer quality depends heavily on what is retrieved. If the website does not provide clear fragments, the system may choose poorly or not choose you at all.
How is RAG handled in AISEO?
Split content into clear, self-contained blocks. Add enough context for each fragment to make sense on its own. Connect entities, sources and trust signals where appropriate.