Task Intelligence Admin Console
Use the Task Intelligence Admin Console to create, train, and deploy machine learning models that predict different types of information for case and interaction records.
From the Admin Console, you can set up predictive models, preview the agent's experience, view when the models are active, and track model performance.
The Admin Console provides tools that you can use to create and implement machine learning models in just a few steps. Each model follows a six-step process.
| 1. Select a model to use as a starting point. | Select the model based on what you want the model to do. For example:
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| 2. Define the purpose of the model. | Tell the model when you want it to make predictions and what you want it to predict. For example, predict the category and priority when a new case is created. |
| 3. Select the data used to train the model. | Train the model using selected data, such as the text in the case short description and description, so it can learn patterns in the data. Then test the model to see how well it works. |
| 4. Assess the model's results. | View test results to see how your well the model performed. These results indicate how a model will perform after being deployed. |
| 5. Select preferences for prediction results. | Add predictions directly to record fields, show predictions as recommendations, or monitor predictions in the background. |
| 6. Deploy the model. | Review your selections and start using the model. |
You can also use the Task Intelligence Admin Console to access related applications. For
more information about using the console, see the following topics: