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Retrieval-Augmented Generation (RAG)
RAG is an architecture where a model retrieves relevant data from external sources before generating a response. This improves accuracy and reduces hallucinations. In analytics, RAG enables AI agents to access semantic layers, metadata, or historical insights before generating answers. Tellius uses RAG techniques for context-rich narratives and query generation.
RAG gives GenAI memory—grounding responses in truth, not guesses.
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