Semantic Search
Retrieval that matches meaning using embeddings instead of exact keywords; foundational for modern RAG and site search.
Semantic search matches queries to content by meaning using embeddings, not just exact keywords. It finds relevant results even when wording differs.
It powers site search, support assistants, and RAG retrieval, improving recall for natural language and long-tail queries.
In stacks, semantic search pairs with filters and re-ranking. It reduces zero-result queries and feeds higher-quality context to downstream systems.
Frequently Asked Questions
How do I build a semantic index?
Chunk content, generate embeddings with a suitable model, store vectors with metadata, and enable filtering.
Do I still need keyword search?
Often yes. Hybrid search (keyword + semantic) balances precision for exact terms and recall for fuzzy language.
How do I handle fresh content?
Embed and index new content frequently or stream updates. Use timestamps to prioritize recent items when relevant.
How can I tune relevance?
Adjust chunk sizes, use metadata filters, and re-rank with click signals or hybrid scores like BM25.
Are embeddings language-specific?
Many models are multilingual, but test for your languages. Use domain-suited models when possible.
How do I evaluate results?
Use judged query-doc pairs, click-through, and task success metrics. Track zero-result rates and off-topic hits.
Can semantic search handle structured filters?
Yes—combine vector similarity with filters on metadata for facets like type, locale, or category.
What infra do I need?
A vector database or engine with ANN search and an embedding service. Monitor latency and index growth.
How do I reduce off-topic results?
Filter by domain, improve chunking, and add negative examples. Use re-ranking to favor authoritative sources.
Agentic AI
An AI approach where models autonomously plan next steps, choose tools, and iterate toward an objective within guardrails.
Agentic Workflow
A sequence where an AI agent plans, executes tool calls, evaluates results, and loops until success criteria are met.
Agent Handoff
A pattern where one AI agent passes context and state to another specialized agent to keep multi-step automation modular.
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