> ## Documentation Index
> Fetch the complete documentation index at: https://wiki.platelunchcollective.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Model Grounding

> Model grounding is the practice of connecting an AI model's outputs to specific, verifiable external data sources — either through retrieval-augmented genera...

*Technical implementation* · *AI Search Infrastructure*

## Definition

Model grounding is the practice of connecting an AI model's outputs to specific, verifiable external data sources — either through retrieval-augmented generation, tool use, or real-time web access — to ensure responses are factually anchored rather than generated purely from training data.

## Why It Matters for AI Search

Model grounding is the mechanism that makes AI search different from AI chat. A grounded model cites sources because it is retrieving and referencing them — not because it is generating plausible-sounding text from memory. For brands, the practical implication is that grounded AI systems are actively looking for content to retrieve, which means the same structural and [entity optimization](https://www.platelunchcollective.com/services/entity-seo) principles that support RAG-based retrieval also support grounded model outputs.

## Related Terms

<CardGroup cols={2}>
  <Card title="Grounding" href="/ai-search-glossary/grounding" />

  <Card title="RAG" href="/ai-search-glossary/rag" />

  <Card title="Retrieval pipeline" href="/ai-search-glossary/retrieval-pipeline" />

  <Card title="Hallucination mitigation" href="/ai-search-glossary/hallucination-mitigation" />

  <Card title="Citation signal" href="/ai-search-glossary/citation-signal" />
</CardGroup>

## Relevant Plate Lunch Collective Services

[Citation-Ready Content](https://www.platelunchcollective.com/services/citation-ready-content)  [AI SEO](https://www.platelunchcollective.com/services/ai-seo)