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| Enabled for | Public preview | General availability |
|---|---|---|
| Users by admins, makers, or analysts | - | 
Mar 6, 2026 |
Business value
Simulation enables administrators to assess how the Case Management Agent performs case enrichment, evaluate the quality of those predictions before enabling the feature in production, and streamline the testing process by reducing the time required for manual validation.
Feature details
Key capabilities
Administrators can run case enrichment simulations using:
- Historical case records
- Uploaded Excel files
- Email or conversation transcripts
Simulation displays the Case Management Agent’s predicted field values based on the selected records or uploaded data.
Simulation using historical case records
Administrators select a set of historical cases to evaluate prediction quality. The condition builder allows filtering. For example, cases from the last seven days or cases related to Contoso Coffee Maker. After running the simulation, administrators can:
- View predicted field values.
- Compare existing field values with predicted values.
- Assess field prediction accuracy.
Simulation using email or conversation transcripts
Administrators can upload emails or conversation transcripts for prediction. Each row in the Excel file represents one email or conversation transcript. The simulation generates predicted field values for each row. Emails or conversations can be extracted from the activity table and uploaded for bulk evaluation.
Simulation using Excel upload
Administrators can upload an Excel file where each row contains a single email or conversation message. The system generates field predictions for each entry. Results help identify how the Case Management Agent would process incoming communications.
Evaluate and improve prediction quality
Simulation results help administrators validate prediction quality before enabling the feature in production. Based on results, administrators can adjust the Case Management Agent configuration. Simulations can be rerun after configuration updates to measure improvement.
This iterative approach helps identify optimization opportunities and ensures reliable predictions before the feature is turned on for the organization.
Geographic areas
Visit the Explore Feature Geography report for Microsoft Azure areas where this feature is planned or available.
Language availability
Visit the Explore Feature Language report for information on this feature's availability.
Related content
Run simulations to evaluate field prediction accuracy in Case Management Agent (docs)