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RAG (Retrieval-Augmented Generation)

A technique that enhances LLM responses by retrieving relevant information from external knowledge bases before generating an answer. RAG grounds AI responses in real, up-to-date data — reducing hallucinations and enabling agents to answer questions about proprietary or domain-specific content.

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