AI models and agents

RAG

Also known as: Retrieval-Augmented Generation

Combining retrieval of relevant materials with generating an answer from them.

A practical example

A system retrieves a product manual section before explaining.

What should I know?

Incorrect sources or retrieval can still produce incorrect answers.

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

RetrievalSelecting documents or passages needed to handle a query.GroundingConnecting generated output to supplied or retrieved information.EmbeddingA numerical representation of content used for similarity comparisons and other model tasks.

Documentation and further reading

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

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