Definition
RAG (Retrieval-Augmented Generation)
RAG is a technique that lets an AI model pull information from a specific, verified knowledge base before generating an answer, reducing incorrect or made-up responses.
Without RAG, an LLM answers purely from what it learned during training, which can be outdated or simply wrong for business-specific questions. RAG solves this by retrieving relevant, current information from your actual documents or database at the moment a question is asked, then having the model base its answer on that retrieved content — the same underlying approach ZAVYANS uses to build chatbots that answer from your verified knowledge base instead of guessing.
