How Grounding differs from RAG, GEO, Hallucination
RAG is the technical pattern (retrieve, then generate). Grounding is the goal (the answer is tied to verifiable sources). RAG is one way to achieve grounding; tool use and structured retrieval are others.
How Mentionwell handles Grounding
- Editorial critic enforces evidence-per-claim so generated articles are themselves well-grounded.
- Markdown mirrors and stable canonicals so engines can ground their answers in Mentionwell-published sources.
Frequently asked questions about Grounding
What does it mean for an LLM answer to be grounded?
The answer is tied to specific retrieved or trusted source documents — usually with citations — rather than being free-generated from training weights.
Why does grounding matter?
Grounded answers hallucinate less, stay current with new information, and let users verify claims. Every AI search product (ChatGPT Search, Perplexity, AI Overviews) is built on grounding.
See also
Ship Grounding-optimized articles automatically
Mentionwell handles Grounding on every published article — alongside the other six optimization targets in this glossary — so you don't have to think about it per post. Drop a domain, approve the first headline, watch the pipeline run.