An exploration of how structured data serves as the ‘Grounding Wire’ for Retrieval-Augmented Generation (RAG) systems, preventing hallucinations and enabling deterministic output from probabilistic models.
Read more →In the rush to build “AI-Powered” search experiences, engineers have hit a wall. They built powerful vector databases. They fine-tuned state-of-the-art embedding models. They scraped millions of documents. And yet, their Retrieval-Augmented Generation (RAG) systems still hallucinate. They still retrieve the wrong paragraph. They still confidently state that “The refund policy is 30 days” when the page actually says “The refund policy is not 30 days.”
Why? Because they are feeding their sophisticated models “garbage in.” They are feeding them raw text stripped of its structural soul. They are feeding them flat strings instead of hierarchical knowledge.
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