Semantic Search

Search your documents and data using natural language meaning, not just keywords — powered by vector embeddings.

Category: Search & Research | Security status: verified | Rating: 4.7/5 | Version: 2.0.0

What Semantic Search does

Semantic Search transforms how you find information in your own data. Instead of exact keyword matches, it understands the meaning behind your queries and finds conceptually relevant results. Powered by state-of-the-art embedding models with hybrid search (vector + BM25), reranking, and intelligent filtering.

Use cases

• Search internal documents by meaning, not just keywords
• Build intelligent FAQ systems that understand user intent
• Create knowledge base search for customer support
• Find similar code snippets across repositories

Install Semantic Search

npx clawhub@latest install semantic-search

Frequently asked questions

How is this different from regular search?

Regular search matches keywords. Semantic search understands meaning — searching 'how to fix auth issues' also finds docs about 'resolving login problems'.

How fast is it?

Sub-100ms for collections up to 1M documents. Larger collections use approximate nearest neighbors for similar speed.

Related OpenClaw skills

• Embeddings Manager
• RAG Pipeline
• Deep Research