Multiple active conversations for Virtual Agent

  • Release version: Xanadu
  • Updated June 24, 2025
  • 2 minutes to read
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    Summary of Multiple active conversations for Virtual Agent

    With the Xanadu release, ServiceNow’s Virtual Agent (VA) supports multiple active conversations simultaneously, each isolated by context. Previously, VA maintained a single chat history shared across all portals, such as Service Portal (SP) and Employee Service Center (ESC). Now, users can engage in independent conversations in different portals with no overlap in chat histories. Large Language Model (LLM) chats are auto-configured per portal, while Natural Language Understanding (NLU) chats require context value setup. Administrators enable LLM assistants per portal through guided setup.

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    Key Features

    • Independent Conversations: Each portal hosts a unique VA chat session, preventing sensitive information leakage between contexts.
    • Context-Based Configuration: Admins can define context values to control message and notification routing per portal.
    • Automatic and Manual Setup: LLM chats auto-configure for multiple conversations; NLU chats need manual context assignments.
    • Elimination of History Carryover Risks: Unlike the prior skiploadhistory method—which closed chats when switching portals—this feature allows seamless multi-portal engagement without exposing past conversations.
    • Notification Routing: Virtual Agent notifications can be sent selectively to multiple portals based on defined contexts.

    Benefits for ServiceNow Customers

    This enhancement allows users to interact with Virtual Agent concurrently across different portals without risk of sensitive data exposure or conversation interruptions. It improves user experience by maintaining relevant context-specific dialogues and keeps incident updates and notifications aligned to the correct portal environment. Administrators benefit from streamlined configuration, avoiding complex scripting while ensuring secure and context-aware VA interactions.

    Implementation Considerations

    • Define portal consumer context values and optionally set a default context.
    • Activate the multiple active conversations system feature.
    • Configure notifications to route to appropriate portals.
    • If default Service Portal context suffices, some configuration steps may be skipped.
    • Ensure NLU context values correspond to portals to properly separate conversations.

    As of the Xanadu release, Virtual Agent (VA) features the ability to have multiple conversations at the same time, separated and directed by chosen context.

    Overview of multiple active conversations for Virtual Agent

    Virtual Agent messages commonly follow one conversation with a shared history that persists on all VA clients, and thus all portals. For example, if you’re conversing with Virtual Agent in a Service Portal (SP) portal context, the same conversation is shown in an Employee Service Center (ESC) portal. The multiple active conversations feature expands the reach of Virtual Agent by eliminating the one-conversation limit. By configuring their Virtual Agent conversations based on context, customers can choose to share or restrict any or all content between concurrent conversations on differing portals.

    Each Virtual Agent conversation is fully independent, with no overlap between chats. For example, a conversation in SP will be entirely different from ESC. Each conversation also has its own transcript. You must set up context values for Natural Language Understanding (NLU) chats, while Large Language Model (LLM) chats are automatically configured for multiple active conversations based on each portal. An administrator can activate an LLM assistant for each portal by using guided setup configurations. (For more information on configuring Virtual Agent conversations, see Conversational Interfaces Guided Setup.)

    Benefits of multiple active conversations

    Previously, if a user was engaged in a conversation with a virtual agent, the chat would take place in a single context. Switching contexts involved a risk of exposing sensitive information by carrying over the entire chat history to the other portal. For example, if you have an HR conversation in the HR portal, then brought up an IT request, the chat continues in the IT portal. However, this request also brings the HR conversation history into the IT portal with it. Alternatively, admins can activate the skip_load_history system parameter to avoid exposure risk, but the initial conversation closes when the chat continues on the IT portal.

    To exclude conversation history between portals, use the following procedure:

    1. Navigate to All > Service Portal > Agent Chat.
    2. Select the Agent Chat Configuration for which you want to set the context value.
    3. In the Server Script window, add the line skip_load_history: true to load conversations without the conversation history.
    Note:
    The script syntax may differ depending on the configuration.

    The multiple active conversations feature bypasses the skip_load_history method, and enables continuous engagement with Virtual Agent chat, by routing selected notifications and topics to their configured contexts only. Users don’t need scripting or extensive customization, and they can conduct conversations without interruption or information exposure in the wrong context. With portals and notification contexts aligned, users receive information appropriate to their context, including incident updates and other relevant data.

    Considerations for using multiple active conversations

    Implementing multiple active conversations should happen in the following order: Admins should define portal consumer context values, set or update a default context, activate the multiple active conversations system, and finally, configure notifications sent to portals. However, if the delivered Service Portal context is sufficient, admins can skip configuring and setting values.

    Topics can be created within a portal context. If the portal context maps to consumer account context, then topics map to consumer account contexts.