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You need to design a generative Al solution that uses a Microsoft SOL Server 2025 database named DB1 as a data source. The solution must generate responses that meet the following requirements: * Ait ' grounded In the latest transactional and reference data stored in D61 * Do NOT require retraining or fine-tuning the language model when the data changes * Can include citations or references to the source data used in the response Which scenario is the best use case for implementing a Retrieval Augmented Generation (RAG) pattern? More than one answer choice may achieve the goal. Select the BEST answer
Correct Answer: C
The best use case for RAG is answering user questions based on company-specific knowledge . Microsoft defines RAG as a pattern that augments a language model with a retrieval system that provides grounding data at inference time, which is exactly what you need when responses must be based on the latest transactional and reference data , must avoid retraining/fine-tuning , and should be able to include citations or references to source data. The other options do not fit as well: * summarizing free-form user input does not inherently require retrieval from DB1, * training a custom model contradicts the requirement to avoid retraining/fine-tuning, * generating marketing slogans is a creative generation task, not a grounding-and-citation scenario. RAG is specifically strong when answers must come from your organization's own changing knowledge.
