Retrieval-augmented generation (RAG) is a cutting-edge method that empowers generative AI models, such as Large Language Models (LLMs), to fetch and incorporate factual information from external sources. RAG empowers these AI models to generate more accurate, relevant, and informative responses. It helps businesses with enhanced CX, reduced overhead costs, and improved efficiency overall.

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