Author: Ammar Sabilarrohman

Large language models have fundamentally transformed how organizations approach text generation, but they continue to grapple with a well-documented and stubborn limitation: they hallucinate. When operating without direct access to verified, up-to-date information, these models can confidently produce plausible-sounding answers that are factually incorrect. To combat this issue, Retrieval-Augmented Generation, commonly known as RAG, emerged…