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A company has a Microsoft Power Platform environment that contains Microsoft Dataverse data. You create a Microsoft Copilot Studio agent named Agent1 that processes the Dataverse data. You discover that Agent1 fails to return relevant or accurate results. You need to improve the quality and reliability of data grounding. What should you do?
Correct Answer: C
If a Copilot Studio agent that uses Dataverse is returning poor or irrelevant results, the most likely issue is weak or inconsistent grounding data . The best corrective action is C. Verify and cleanse the Dataverse data. Why C is correct: * Grounded AI quality depends heavily on source data quality * Incomplete, inconsistent, duplicated, outdated, or badly structured Dataverse records will lead to poor answers * Cleansing and validating the data improves both relevance and reliability without requiring unnecessary model changes Why the other options are not correct: * A. Use an adaptive card in Agent1 Adaptive cards improve UI interaction, not grounding quali ty. * B. Add example user inputs to the training data of Agent1 This may help intent handling, but the issue here is inaccurate grounding from Dataverse. * D. Retrain Agent1 Copilot Studio grounding problems are usually solved by improving source data, not ret raining the agent.
