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The use of a retrieval-augmented generator (RAG) model in an AI system is important in the sense that it enables the generative AI models to acquire information from external sources during the generation of natural language responses. As opposed to the conventional language model where the information is acquired from training data, the rag model retrieves information from the documents or databases at the time of the query. The use of the rag model becomes beneficial when companies are dealing with specific information.