Create a model to predict similar open incidents

Use the Task Intelligence for CSM to create and train a machine learning model that identifies similar open incidents. The model analyzes similar open incidents data to suggest relevant incident records when working on a current open incident, helping agents resolve issues faster. The plugin includes a ready-to-train model for predicting similar cases and also lets you create custom models tailored to your specific use cases.

Before you begin

• Ensure that the Task Intelligence for Customer Service plugin is installed.
• Ensure that your instance contains sufficient open incident records (minimum 10,000 recommended) for meaningful training.
• Role required: ml_admin, ti_admin

Set up the prediction model

Procedure

1. Navigate to All > Task Intelligence for Customer Service > Setup.
   The Task Intelligence Admin Console displays.
2. On the Similar Open Incidents card, select Ready to train.
   The model opens in a guided setup flow. The Define the purpose screen appears.
3. Define the purpose:
   1. Review the pre-filled Model name.
   2. The Prediction table and Training table are pre-selected as Cases and Incidents, respectively.
      These values are fixed and cannot be edited.
   3. Select Save & Continue.
      The Train your model screen appears.
4. Train your model:
   1. The Model name and Prediction table fields are pre-filled and cannot be edited.
   2. Optional: Apply Conditions to filter the training data.
   3. In the Prediction table field, select fields such as Description and Short description that the model should use to identify similarities.
   4. In the Training table section, select matching or relevant fields that help the model compare open incidents.
   5. Choose the language for training.
   6. Set the Update frequency.
   7. Review the Number of records.
      If needed, select the Load records icon to reload.
   8. Optional: Enable Auto-retrain to allow retraining the model on a set schedule.
   9. Select Launch training.
   10. Once training starts, select View current results to preview sample outputs.
       The Assess and define screen appears.
5. Assess and define:
   1. Review the Estimated number of records used for training.
   2. In Prediction preference, select one of the following options:
      • Recommendations – Recommends similar open incidents (selected by default).
      • Monitor only – Runs the model in the background without displaying recommendations. You can analyze the logged data before enabling recommendations.
      • Turn off predictions – Disables all predictions for this model.
   3. Select Save & Continue.
      The Deploy your model screen appears.
6. Deploy your model:
   1. Review your setup and training summary and then select Deploy to activate the model.
      A confirmation message appears when deployment is complete.
   Result

   Once deployed, similar open incidents are displayed in the Recommended Actions section under the Suggested Actions tab when an agent opens a case that helps them resolve cases faster using related issues and prior solutions.