What is Grounding?
Grounding is the process by which an LLM ties its generated answer to specific retrieved source documents, rather than answering purely from parametric memory. A grounded answer is one the model can attribute — meaning it points to (and often cites) the passage it lifted the claim from. Modern answer engines (ChatGPT Search, Perplexity, Google AI Overviews, Claude with web tools) are all grounded systems: the retrieval layer decides which sources are eligible, and the generation layer weaves them into the answer. For PR teams the takeaway is unambiguous — being one of the grounding sources is the entire game. A brand missing from the retrieval set can't be cited no matter how good the pitch was six months ago. Crackle PR engineers both sides of the grounding equation: earned media in outlets LLMs retrieve from, and on-site authority surfaces (glossary, schema, quote density) that make the client the cleanest available source to ground against.
“Grounding is the moment the LLM decides who gets credit. Everything upstream — the pitch, the placement, the schema — is just fighting to be one of the sources the model reaches for.”
Related terms
RAG (Retrieval-Augmented Generation)
An architecture where an LLM retrieves fresh source documents at query time and grounds its answer in them.
AI Citation
A reference to your brand inside an AI-generated answer, typically with a link back to a source URL.
AI Source Ranking
The implicit ranking LLMs apply when selecting which retrieved sources to cite in an answer.
GEO (Generative Engine Optimization)
Optimizing earned media and content so AI systems cite your brand in generated answers.
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