Retrieval-Augmented Generation (RAG)
RAG is an AI architecture that optimizes LLM output by referencing an authoritative, external knowledge base outside of its initial training data before generating a response.
How it works & Why it matters
In 2026, RAG is the gold standard for enterprise AI. Unlike 'pure' LLMs which rely on static training data, RAG systems query a vector database in real-time. This eliminates hallucinations and ensures that AI responses are grounded in your company's specific, up-to-date documentation. For businesses, this means AI Chatbots that actually know your inventory, pricing, and specific SOPs without constant retraining.
Master Retrieval-Augmented Generation (RAG) for your business
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