> ## 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.

# Knowledge Cutoff

> A knowledge cutoff is the date beyond which a language model's training data does not extend.

*Core concept* · *AI Search Infrastructure*

## Definition

A knowledge cutoff is the date beyond which a language model's training data does not extend. Events, content, or developments that occurred after the cutoff are not part of the model's base knowledge and must be supplied through retrieval-augmented generation or real-time search.

## Why It Matters for AI Search

Knowledge cutoffs create predictable gaps in AI representations of brands and industries. A company that launched after a model's cutoff, or that made significant changes after it, may be absent or inaccurately represented in that model's base knowledge. Understanding cutoffs helps explain why a brand appears differently across different AI platforms — and why real-time [retrieval optimization](https://www.platelunchcollective.com/services/citation-ready-content) matters alongside training corpus presence.

## Related Terms

<CardGroup cols={2}>
  <Card title="Training corpus" href="/ai-search-glossary/training-corpus" />

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

  <Card title="Foundation model" href="/ai-search-glossary/foundation-model" />

  <Card title="Pre-training" href="/ai-search-glossary/pre-training" />

  <Card title="AI Search Ecosystem" href="/ai-search-glossary/ai-search-ecosystem" />
</CardGroup>

## Relevant Plate Lunch Collective Services

[AI SEO](https://www.platelunchcollective.com/services/ai-seo)  [AI Search Visibility Assessment](https://www.platelunchcollective.com/services/context-map)  [Context Map](https://www.platelunchcollective.com/services/context-map)