Apply Natural Language Understanding (NLU) models that enable your virtual agent to
understand user statements in automated conversations. An NLU model provides information that
your virtual agent uses to determine what users want to do and to extract relevant values from
their input. With NLU, your virtual agent can offer a more natural and engaging conversational
How NLU models work in Virtual Agent
NLU models are trained to understand statements a user might make during a conversation,
and to relate them to a task that a user wants to perform. Virtual Agent uses the following
information in an NLU model to understand and process user requests:
- Intents: What a user wants to do, for example perform an action such as submitting a
service ticket or getting an update on an order.
- Utterances: The different ways that a user expresses an intent.
- Entities: The object or context for an action, such as a laptop, case number, or an
For details on intents, utterances, and entities defined in NLU models and how they work in
machine learning, see ServiceNow Natural Language
When you create or update topics in Virtual Agent Designer, you identify the
NLU model and intent that Virtual Agent uses to find the appropriate conversation topic for fulfilling the intent.
supports models from
Understanding service or the IBM Watson Assistant service. You can use:
- ServiceNow NLU models that you
create using ServiceNow
ServiceNow provides prebuilt
(read-only) NLU models for the Customer Service Management, HR Service Delivery, and ITSM applications, along
with predefined topics. You can use the intents defined in these prebuilt models and
reuse them when you create your own models.
- NLU intents and entities created in IBM Watson Assistant, only if you're
using IBM Watson Assistant as your NLU service provider.
Note: Virtual Agent supports only
one NLU service provider per instance.
With NLU models, your virtual agent can
- Perform topic discovery
- Extract entity values
- Handle conversation switching in a conversation session
Virtual Agent processes user
utterances (statements associated with a specific intent) to launch the appropriate
conversation topic. Each topic has a single intent that you specify in Virtual Agent Designer.
During the topic discovery process (matching intents to topics), Virtual Agent
returns the most relevant
topics for a user's request.
topic discovery process returns these results to a user:
- Single match: When a user utterance directly matches an intent (topic), the topic runs
- Multiple matches: When a user utterance matches more than one intent, Virtual Agent returns a choice list
of the relevant matches so that the user can choose the appropriate topic.
- No matches: When the virtual agent does not understand a user utterance, it
automatically displays a fallback message. The user can select a topic or enter a
The fallback response runs automatically in the conversation when the virtual
agent cannot match a topic to the intent. For details on how the fallback response
(called the fallback setup topic) works, see Select Virtual Agent setup topics
With NLU models, Virtual Agent can determine when user statements in a conversation contain
important information to fulfill a task or goal. Entities identify the information that
Virtual Agent can extract from the conversation, such as an object or a person's name. To
extract the appropriate values, Virtual Agent uses the entity information associated with an
intent defined in the NLU model. The input controls that you add to your conversation also
have associated NLU entity properties that you can set. Virtual Agent matches the extracted
entity with the input control variable that fulfills or completes the action, and skips the
prompts asking the user for additional
Users engaged in a virtual agent conversation can switch topics anytime during the
conversation. For example, a user could be updating an item in their employee profile, but
before completing the update, that user might ask to order an item instead. Your virtual
agent can find and run the appropriate topic based on the user's request. You can enable
users who switched topics to resume the original conversation.
Or a user can ask a casual question (called small talk) that might be unrelated to the
original request. By reviewing the intents defined in the NLU model, Virtual Agent can match and launch the
appropriate conversation for the switched topic.
Get started with NLU in Virtual Agent
After you activate the plugins for Glide Virtual Agent and the predefined
topics for the CSM, HR Service Delivery, and ITSM business applications, prepare
your NLU models and enable NLU for your instance.
Implementing NLU involves these steps:
- Prepare your NLU models.
If you're using ServiceNow
NLU, review the prebuilt NLU models (provided with the Customer Service Management, HR Service Delivery, and ITSM applications)
in ServiceNow Studio.
Consider whether you want to reuse intents from these models when creating your
own NLU models.
Studio to create, train, and publish your NLU models.
- If you're using IBM Watson Assistant as an NLU
service provider, configure the IBM Watson Assistant Intent and Entity integration.
- In Virtual Agent
Settings, enable NLU and select your NLU service provider.
- Before you create or update topics, preview the predefined
ServiceNow topics in Virtual Agent Designer. Determine
whether you want to use any of the topics, then duplicate and publish them as needed.
- As you create or update topics in Virtual Agent Designer, follow the
steps for creating a
topic. Note these details:
When you are ready to deploy a topic, change the state to
Active and publish the topic.
- Verify that you are in the appropriate application scope before you create or
update a topic. For example, if you are creating ITSM topics, verify that you are in
the ITSM Virtual Agent Conversations scope (and not the scope
for the ITSM NLU Model for Virtual Agent Conversations).
- Select the NLU Model and Associated
Intent for the topic in the Topic Properties
page. And if topic switching is allowed in the conversation session, enable
Resume topic flow.
Note: A topic can have only one intent. Once you select an intent for a topic, the
intent is no longer available for use in other topics.
- Set the NLU entity properties in the property sheet for each input control that
you add to the conversation flow. The entity properties identify the entity
associated with the node, a switch for allowing text input for the control (prompt),
and another switch for confirming the slot-filled entity value that Virtual Agent
- Test the topic.