--- title: Create a model to predict similar open incidents description: 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. locale: en-US canonical_url: https://www.servicenow.com/docs/r/australia/customer-service-management/csm-task-intel-create-model-open-incidents.html release: australia topic_type: task last_updated: "2026-03-12" reading_time_minutes: 2 breadcrumb: [Configure, Task Intelligence for Customer Service, Machine learning solutions, Implement Intelligence, Configure, Customer Service Management] --- # 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. 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. 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.