Definition

What is Semantic Search?

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A search method that finds results based on meaning and intent rather than exact keyword matching.

Semantic search uses vector embeddings to represent text as mathematical points in space, allowing it to find conceptually related content even when the exact words differ. Wire includes semantic search on all context containers, so agents can find relevant information using natural language queries.

Related RAG (Retrieval-Augmented Generation) Context Container

Further reading

Articles about Semantic Search

What chunk size should you use for RAG?

Studies disagree on the best chunk size for RAG: one found 100 tokens with zero overlap won. What the research supports, and the bigger lever most guides miss.

Knowledge graphs vs RAG: when graphs actually win

Knowledge graphs vs RAG: graph retrieval wins multi-hop reasoning and global summarization, but vector RAG matches it on simple lookups at far lower cost.

Chunking Strategies Decide What Context AI Sees

Chunking strategies decide which context reaches your AI. How fixed-size, semantic, and late chunking change retrieval accuracy, with 2026 benchmark data.

One job per tool: why adding wire_navigate cut agent calls 24%

We restructured Wire's MCP surface from 2 overloaded tools to 3 single-purpose ones. The counterintuitive result: adding a tool cut total calls 24%.

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All terms

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Agent Drift Agent Reliability Agentic Retrieval AI Agent AI Hallucination AI Second Brain Chunking Context as a Service Context Bloat Context Compression Context Container Context Drift Context Offloading Context Engineering Context Poisoning Context Portability Context Pruning Context Rot Context Window Epistemic Provenance Fine-Tuning Knowledge Graph MCP Resources MCP Server MCP (Model Context Protocol) Multi-Agent System Prompt Caching RAG (Retrieval-Augmented Generation) Prompt Engineering Semantic Search Structured Context Tool Poisoning Wire

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