> ## 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.

# Neural Search

> Neural search is a search methodology that uses neural networks — specifically deep learning models — to understand the meaning of queries and documents rath...

*Technical implementation* · *AI Search Infrastructure*

## Definition

Neural search is a search methodology that uses neural networks — specifically deep learning models — to understand the meaning of queries and documents rather than matching on keyword frequency. It powers semantic search, dense retrieval, and AI-generated answer systems.

## Why It Matters for AI Search

Neural search is the technical foundation of modern AI search. When ChatGPT or Perplexity retrieves content to ground an answer, it is using neural search — computing semantic similarity between a query and candidate documents using learned representations. Content that is semantically rich, clearly structured, and topically coherent performs well in neural search because neural models reward meaning-based relevance over keyword repetition.

## Related Terms

<CardGroup cols={2}>
  <Card title="Dense retrieval" href="/ai-search-glossary/dense-retrieval" />

  <Card title="Embedding" href="/ai-search-glossary/embedding" />

  <Card title="Semantic search" href="/ai-search-glossary/semantic-search" />

  <Card title="Semantic relevance" href="/ai-search-glossary/semantic-relevance" />

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

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