Natural Language Understanding topic discovery logic in Virtual Agent

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  • Updated July 31, 2025
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    Summary of Natural Language Understanding Topic Discovery Logic in Virtual Agent

    This document details how the Virtual Agent utilizes Natural Language Understanding (NLU) to discover topics and return intents to users effectively. Understanding these mechanisms allows ServiceNow customers to optimize user interactions within Virtual Agent.

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    Prerequisites for Topic Discovery

    • The topic must be published and active, with relevant values in the Topics table set to true.
    • The topic must be discoverable, and any configured roles must be assigned to the requester.
    • The NLU model for the topic must support the session language.

    NLU Topic Discovery Logic

    Virtual Agent sends a prediction request to the NLU provider, including the user's utterance and the relevant NLU model IDs. Based on the predictions, it can:

    • Automatically select the best topic using a confidence score.
    • Prompt the user to choose from a list of matched topics.
    • Fallback to keyword searches if no matches are found and backup keywords are enabled.

    Virtual Agent NLU Confidence Scores

    Confidence scores are crucial for determining intent matches. Customers can set the confidence threshold through the ServiceNow NLU integration settings. The logic for intent selection includes:

    • Auto-selecting the highest predicted intent.
    • Providing a list of topics if auto-selection isn't applicable.
    • Fallback to keyword searches if no intents meet the confidence threshold.

    Mid-Topic NLU Topic Discovery Logic

    During an active conversation, if a user enters a phrase that triggers a different intent, Virtual Agent can switch topics accordingly. For example, while discussing a date of birth, if the user mentions wanting to view incidents, Virtual Agent will re-evaluate and transition to the relevant topic.

    Understand how Virtual Agent returns intents and how it selects which intents to show to the user.

    Prerequisites for topic discovery

    Virtual Agent can discover a topic when the following conditions are met:
    • The topic must be published and active.

      In the Topics [sys_cs_topic] table, the Active, Published, and Is Topic Discoverable values are set to true.

      Note:
      The Is Topic Visible column does not affect topic discovery.
    • The topic must be discoverable.
    • Topic conditions must evaluate to true at runtime.
    • If any roles are configured for the topic, the requestor must have at least one of those roles.
    • The topic's NLU model must have a binding for the session language.

    NLU topic discovery logic

    Virtual Agent sends a prediction request to the NLU provider. The request contains the utterance and all registered NLU model IDs that are bound to the session language. Matches return NLU intents that correspond with a topic. Virtual Agent then responds in one of the following ways:
    • Automatically selects a topic for the requester, based on the confidence score.
    • Prompts the requester to pick a topic from the returned list of matches.
    • Finds no matching topics.

    If no matches are found but backup keywords are enabled (the com.glide.cs.nlu.keywords.enabled property is true), Virtual Agent searches for a topic based on keywords.

    Virtual Agent NLU confidence scores

    Virtual Agent uses confidence scores to return predicted intents. To set the confidence value:

    1. Navigate to Conversational Interfaces > External NLU Integrations > Drivers.
    2. Select ServiceNow NLU. You can also select All and enter open_nlu_driver.list.
    3. In the Intent Confidence Threshold field, enter the confidence threshold.

    If an intent's confidence score is greater than or equal to the configured threshold, Virtual Agent considers it a good match.

    Virtual Agent uses the following logic when selecting intents:
    • Auto-selects the highest predicted intent.
      This occurs when only one intent is matched, or in the event of a tie-breaker, when the next closest match is a distant second.
      Note:
      If ServiceNow NLU is used and the Intent Confidence Delta field in the ServiceNow NLU driver table (open_nlu_driver.list) is set to 0, there can be no tiebreaker.
    • Returns a topic list for the requester to choose from.

      This occurs if auto-select is not applicable. The length of the list is determined by the com.glide.cs.max_number_display_topics system property.

    • No intents are matched.

      When zero NLU Intents are predicted with a confidence score greater than or equal to the configured threshold, Virtual Agent falls back to a keyword search if configured. (The com.glide.cs.nlu.keywords.enabled and com.glide.cs.nlu.keywords.include_topics_bound_to_lang system properties are true).

    Mid-topic NLU topic discovery logic

    While a topic is running, the requester can enter an utterance or phrase that results in a topic switch. For example:

    1. The requester is in a Virtual Agent conversation, and Topic A is running.
    2. Topic A prompts the user to enter their date of birth.
    3. Instead of choosing a date, the requester types, "I want to view my Incidents."
    4. Virtual Agent can't resolve this phrase to a date, so it issues an NLU prediction request.
    5. The NLU predictor returns Intent B, and Virtual Agent sees that Topic B is bound to Intent B.
    6. Virtual Agent switches the conversation to Topic B, which then presents information to the requester about their incidents.