Document Intelligence for Customer Service

  • Release version: Australia
  • Updated March 12, 2026
  • 3 minutes to read
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    Summary of Document Intelligence for Customer Service

    Document Intelligence for Customer Service allows agents to extract relevant information from emails and case attachments, such as credit card numbers and customer addresses, and automatically populate these fields in case records. This feature enhances case management efficiency by reducing manual data entry.

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    Key Features

    • Human in the Loop (HITL): Agents can review and correct extracted values directly through the Document Intelligence interface, helping to refine the model and improve its performance over time.
    • Predicted Field Values: Fields containing extracted data are marked with an AI icon and labeled as "Predicted from DocIntel," providing additional context for agents.
    • Prediction Banner: A banner indicates fields with predictions needing review, enhancing visibility and ensuring agents address unverified predictions promptly.
    • DocIntel Admin Experience: Offers an intuitive interface for creating and managing document processing use cases and monitoring performance, accessible via the Task Intelligence Admin Console.
    • Document Classification: Administrators can create classification use cases to categorize documents, enabling the AI to learn and apply relevant classifications effectively.

    Key Outcomes

    By utilizing Document Intelligence for Customer Service, organizations can expect improved accuracy in data entry, enhanced agent productivity, and a streamlined workflow for case management. Continuous training of the AI model through agent interactions leads to ongoing improvements in the feature's effectiveness.

    Use the Document Intelligence for Customer Service feature to extract relevant information from email and case attachments, such as credit card numbers or customer addresses, and add that information to cases.

    Figure 1. Document Intelligence for Customer Service extracted fields
    Case details tab displaying Predicted or Predicted from Docintel labels under certain field values, such as Account or Vendor name, alerting agents that the information was extracted by Document Intelligence.

    Agents can review values for extracted fields and make corrections as needed by accessing the Document Intelligence interface directly from the case. From this interface, agents can confirm correct values, fix incorrect values, and continue to train the model. This HITL/Human In the Loop interaction of verifying the recommended values enables agents to refine the model and continually improve performance.

    Predicted field values

    In CSM Configurable Workspace and Core UI, the fields on the Case form that contain Document Intelligence predicted values are identified with an AI icon (AI icon) and label. These fields also include an information icon that displays a message with additional context about the predicted values.
    Note:
    The system displays the AI icon automatically. The agent doesn’t need to refresh the record page.

    In CSM Configurable Workspace and Core UI, the fields on the Case form that contain Document Intelligence predicted values are identified with the message Predicted from DocIntel.

    Prediction banner

    The system displays a banner at the top of a case record that contains one or more Document Intelligence field predictions. The banner is displayed:
    • When there is at least one field with an auto-filled prediction from a categorization model.
    • When one or more of the extracted fields haven’t been reviewed by the agent.
    • When the fields are being updated.
    • When the fields can’t be generated or predicted.
    Once an agent reviews the field, the banner is removed.

    The banner is displayed for records in the Case table, extensions of the Case table, and interaction records. The banner is displayed in the Core UI and CSM Configurable Workspace.

    The banner can be enabled or disabled by the sn_csm_ml_task.ui.banner.enabled system property.

    DocIntel Admin experience

    The DocIntel Admin experience provides an easy-to-use interface that you can use to do the following:
    • Create and configure document processing use cases
    • Monitor the performance of Document Intelligence solutions

    The DocIntel Admin experience is available with the Document Intelligence Admin (com.snc.docintel_admin) store app. This app automatically activates the flows and properties required by Document Intelligence for Customer Service.

    Access the DocIntel Admin experience through the Task Intelligence Admin Console:
    1. Navigate to Task Intelligence for Customer Service > Setup.
    2. In the Explore related applications section of the console, select Open DocIntel in the Document Intelligence card.
      Note:
      If Document Intelligence Admin isn’t installed, the home page displays a link that you can use to download and activate the application.
    For more information, see the following topics: .

    Use Cases list

    From the DocIntel Admin experience, select Use Cases in the header to display a list of the use cases. The Use Cases list uses a default filter with an OR condition to show use cases for:
    • Application = Task Intelligence for Customer service -or-
    • MLUC ID = MLUC CSM-00003
    Note:
    The user can’t modify these filter conditions from the advanced view.

    Each use case has an MLUC ID number that is automatically assigned when the use case is created. This ID number is used for machine learning usage tracking. The Task Intelligence for Customer Service application manages the MLUC ID for Document Intelligence for Customer Service use cases.

    Document classification

    With the system administrator role, you can create document classification use cases and define the classes or categories for the AI to detect and apply to documents. This process is useful in situations where there are multiple types of documents that must be evaluated.

    Set up a document classification use case in the following steps.
    1. Create a document classification use case.

      Define the name and properties for the use case.

    2. Create a document class.

      Define the classes or categories that the AI learns to detect and apply to documents.

    3. Create a document task for document classification and upload sample documents for each class.
    4. Train a use case.

      Initiate a training job to provide user inputs from completed document tasks to the AI for continuous improvement.