What is a RAG Model?

As tech consultants, what do we need to know about RAG?

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A Retrieval-Augmented Generation (RAG) model is a type of artificial intelligence that blends two powerful approaches: retrieval of information from external sources and generative AI. Unlike traditional language models, which rely solely on pre-trained knowledge, RAG models actively pull in up-to-date, relevant data from a knowledge base or database before generating a response.

Here’s why this matters for consultants in tech: RAG models reduce “hallucinations” (when AI confidently gives incorrect answers) by grounding outputs in real, verifiable content. For example, instead of relying on outdated training data, a RAG model can query a company’s internal documents, reports, or case studies, then weave that retrieved knowledge into its answers.

For female tech consultants working with clients, this means smarter, more reliable AI applications. Whether you’re advising on digital transformation, knowledge management, or client communication tools, RAG can provide a strategic edge. Imagine a client-facing chatbot that not only explains a product but pulls the latest compliance guidelines or market research directly into the conversation.