AI Visibility Glossary
RAG (Retrieval-Augmented Generation)
Why it matters
Because RAG pulls from retrievable content, being retrievable and citation-worthy is how you get into AI answers. It makes your published content directly influence AI responses.
How to measure it
Assess whether your key pages are crawlable, well-structured, and answer-first, so retrieval systems can find and lift them.
Measure your AI visibility
See how AI engines cite and recommend your brand, scored on eight signals across every major engine. Free.
Related terms
Grounding is when an AI engine bases its answer on retrieved, real-world sources rather than relying only on its trained memory. Grounded answers cite the pages the model pulled from, often via live web search.
GEO, or Generative Engine Optimization, is the practice of earning citations and mentions inside generative AI responses. It focuses on becoming a source the model trusts and pulls from when it composes an answer, rather than ranking in a traditional index.
Citation rate is how frequently AI engines cite a brand or its website as a source when answering questions in its category. A high citation rate means the engine repeatedly leans on your content to ground its answers.
llms.txt is a proposed standard file, placed at a site's root, that gives AI engines a clean, markdown summary of what the site is and where its key content lives. It helps models understand and accurately represent a brand.