RAG improves LLM output accuracy by grounding generative AI in enterprise data, helping to mitigate hallucinations that occur with standard LLMs.
Bonaci highlights that using RAG ensures generative AI considers accurate enterprise data, greatly reducing the risk of hallucinations and improving reliability.
RAG provides LLMs with access to an enterprise’s specific information set, ensuring that the generated content is pertinent and contextually relevant.
As enterprises adopt generative AI, leveraging RAG is critical, allowing precise and reliable insights that are tailored to specific organizational needs.
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