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QAT Global Insights Blog
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From Guessing to Knowing: How Retrieval-Augmented Generation (RAG) Builds Trustworthy Enterprise AI
At QAT Global, we believe enterprise AI must be built on accuracy, transparency, and trust. As organizations explore Large Language Models (LLMs), one of the most practical ways to make them reliable for real-world use is through Retrieval-Augmented Generation (RAG). In this guide, Ray Carneiro, QAT Global’s Director of Engineering and Architecture, explains how RAG works and why it matters, when to use it, and how business and technology leaders can implement to drive business success.
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