AI models and agents

Semantic search

Also known as: semantic search

Selecting results using meaning and context, not only identical words.

A practical example

A shipping question finds a document describing delivery.

What should I know?

Semantic search still requires relevance assessment.

AI models and agents in practice

A model processes information; the application defines tools and permissions. Reliable answers require good sources and verification. Actions involving accounts, content, and orders must stay within the granted scope.

Related Semly features

See where this concept applies when working with Semly.

Semly MCPConnect Semly data and tools to your AI assistant. Analyze reports and work with Leon in a conversation.Websites for AI agentsShare structured company knowledge and inquiry forms through an agent channel.

Related terms

EmbeddingA numerical representation of content used for similarity comparisons and other model tasks.RetrievalSelecting documents or passages needed to handle a query.RelevanceHow well information matches the user's need, context, and constraints.

Documentation and further reading

Definition prepared by Semly. Standards and behavior are described by their creators:

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