# Vector Search (Semantic Search)

Source: https://customlabs.io/glossary/vector-search/
Updated: 2026-09-13

Retrieval

# Vector Search (Semantic Search)

Also known as semantic search, similarity search

Vector search finds the nearest matches to a query by comparing embeddings, not exact keywords.

It lets a RAG pipeline surface a passage about "cancel my plan" for a user who typed "stop billing me."

In production it is usually paired with metadata filters and a reranker.

Raw nearest-neighbor results alone are rarely precise enough to hand straight to the model.

[Insight: Your RAG demo lied to you](https://customlabs.io/insights/your-rag-demo-lied/)[Capabilities](https://customlabs.io/capabilities/)

[← Back to the full glossary](https://customlabs.io/glossary/)

## Related terms

[Retrieval-Augmented Generation (RAG) Retrieval-Augmented Generation (RAG) retrieves relevant passages at query time and feeds them into an LLM's context.](https://customlabs.io/glossary/retrieval-augmented-generation/)[Embeddings Embeddings are numeric vectors that place similar content close together in vector space.](https://customlabs.io/glossary/embeddings/)[Chunking Chunking splits source documents into smaller passages before embedding, so retrieval returns focused text.](https://customlabs.io/glossary/chunking/)