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The Evolution of Enterprise AI: How Agentic RAG is Overcoming the Limitations of Naive Retrieval Systems
Large language models have fundamentally transformed how organizations approach text generation, yet they remain plagued by a well-documented and persistent vulnerability: hallucinations. When operating without direct access to verified, up-to-date information, these powerful models can confidently produce plausible-sounding answers that are factually incorrect. To combat this limitation, Retrieval-Augmented Generation, commonly known as RAG, emerged as…
