This white paper explores how Retrieval-Augmented Generation (RAG) is redefining intelligent enterprise applications. RAG enhances LLMs with real-time, context-rich data, improving accuracy, reducing hallucinations, and enabling enterprise-grade outputs. It merges generative AI with search, making applications more responsive and domain-aware. Key benefits include cost efficiency, reduced model size, and explainability. The paper outlines RAG’s architecture, use cases like customer support and knowledge management, and its role in evolving from standalone chatbots to deeply integrated enterprise systems that drive productivity and decision-making.

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