\(Legacy\) Natural Language Understanding
ServiceNow® Natural Language Understanding (NLU) provides an NLU Workbench and an NLU inference service that you can use to enable the system to learn and respond to human-expressed intent. By entering natural language examples into the system, you help it understand word meanings and contexts so it can infer user or system actions.
Overview of Natural Language Understanding
Starting with the Brazil release, Natural Language Understanding is being prepared for future deprecation. It will be hidden and no longer activated on new instances but will continue to be supported. For details, see the Deprecation Process [KB0867184] article in the Now Support Knowledge Base.
For an overview of Natural Language Understanding, see (Legacy) Exploring Natural Language Understanding.
NLU terminology
In NLU parlance, these terms identify the key language components the system uses to classify, parse, and otherwise process natural language content.
-
Intent
Something a user wants to do or what you want your application to handle, such as granting access.
-
Utterance
A natural language example of a user intent. For example, a text string in an incident's short description, a chat entry, or an email subject line. Utterances are used to build and train intents and should therefore not include several or ambiguous meanings or intents.
-
Entity
The object of, or context for, an action. For example: a laptop, a user role, or a priority level.
-
System entity
These are predefined in an instance and have highly reusable meanings, such as date, time, and location.
-
User defined entity
These are created in the system by users and can be built from words in the utterances they create.
-
Common Entity
A context commonly used and extracted via a pre-defined entity model, such as currency, organization, people, or quantity.
-
Vocabulary
Vocabulary is used to define or overwrite word meanings. For example, you can assign the synonym “Microsoft” to the acronym “MS”.
-
NLU Model
A collection of utterance examples and their associated intents and entities that the system uses as a reference to infer intents and entities in a new utterance. The NLU Workbench comes with pre-built NLU models for specific business units, such as an ITSM model. You can also create custom models.
NLU Workbench
Use the NLU Workbench to create morphological representations of human language. These models enable you to create intents and entities expressed in natural language utterances. Any ServiceNow application can invoke an NLU model to get an inference of intents and entities in a given utterance.
Using the nlu_admin role, you build your models in the NLU Workbench, where you create, train, test, and publish them iteratively.
For information on how to build and use an NLU model, see: Create an NLU model.
NLU inference service
Natural Language Understanding provides an NLU inference service that helps the system to understand natural language and drive intelligent actions. This service trains and predicts intents and entities for a given user utterance in your model so that its text translates into machine-understandable formats, such as APIs and parameters.
The system uses an inference API to train NLU algorithms by using sample record data to identify intents and entities that are strong candidates for accurate prediction.
NLU model consumption
Other ServiceNow® applications consume NLU model output, such as Virtual Agent.
For example, Virtual Agent administrators can configure a Virtual Agent Designer conversation flow to consume NLU models so that agent chatbots can better understand user statements in the conversation. For more information on how Virtual Agent consumes NLU models, see: Natural Language Understanding (NLU) topic discovery in Virtual Agent.
Get started
## Troubleshoot and get help---
title: \(Legacy\) Natural Language Understanding
description: ServiceNow Natural Language Understanding \(NLU\) provides an NLU Workbench and an NLU inference service that you can use to enable the system to learn and respond to human-expressed intent. By entering natural language examples into the system, you help it understand word meanings and contexts so it can infer user or system actions.
locale: en-US
canonical_url: https://www.servicenow.com/docs/r/intelligent-experiences/nlu-service/nlu-landing.html
release: brazil
product: NLU Service
classification: nlu-service
topic_type: reference
last_updated: "2026-09-10"
reading_time_minutes: 5
breadcrumb: [Machine learning and natural language capabilities, Enable AI Experiences]
---
# \(Legacy\) Natural Language Understanding
ServiceNow® Natural Language Understanding \(NLU\) provides an NLU Workbench and an NLU inference service that you can use to enable the system to learn and respond to human-expressed intent. By entering natural language examples into the system, you help it understand word meanings and contexts so it can infer user or system actions.
## Overview of Natural Language Understanding
Starting with the Brazil release, Natural Language Understanding is being prepared for future deprecation. It will be hidden and no longer activated on new instances but will continue to be supported. For details, see the [Deprecation Process \[KB0867184\]](https://support.servicenow.com/kb_view.do?sysparm_article=KB0867184) article in the Now Support Knowledge Base.
For an overview of Natural Language Understanding, see [\(Legacy\) Exploring Natural Language Understanding](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/brazil/markdown/intelligent-experiences/nlu-service/nlu-explore.md).
## NLU terminology
In NLU parlance, these terms identify the key language components the system uses to classify, parse, and otherwise process natural language content.
- **Intent**
Something a user wants to do or what you want your application to handle, such as granting access.
- **Utterance**
A natural language example of a user intent. For example, a text string in an incident's short description, a chat entry, or an email subject line. Utterances are used to build and train intents and should therefore not include several or ambiguous meanings or intents.
- **Entity**
The object of, or context for, an action. For example: a laptop, a user role, or a priority level.
- **System entity**
These are predefined in an instance and have highly reusable meanings, such as date, time, and location.
- **User defined entity**
These are created in the system by users and can be built from words in the utterances they create.
- **Common Entity**
A context commonly used and extracted via a pre-defined entity model, such as currency, organization, people, or quantity.
- **Vocabulary**
Vocabulary is used to define or overwrite word meanings. For example, you can assign the synonym “Microsoft” to the acronym “MS”.
- **NLU Model**
A collection of utterance examples and their associated intents and entities that the system uses as a reference to infer intents and entities in a new utterance. The NLU Workbench comes with pre-built NLU models for specific business units, such as an ITSM model. You can also create custom models.
## NLU Workbench
Use the NLU Workbench to create morphological representations of human language. These models enable you to create intents and entities expressed in natural language utterances. Any ServiceNow application can invoke an NLU model to get an inference of intents and entities in a given utterance.
Using the nlu\_admin role, you build your models in the NLU Workbench, where you create, train, test, and publish them iteratively.
For information on how to build and use an NLU model, see: [Create an NLU model](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/brazil/markdown/intelligent-experiences/nlu-service/create-nlu-modelx.md).
## NLU inference service
Natural Language Understanding provides an NLU inference service that helps the system to understand natural language and drive intelligent actions. This service trains and predicts intents and entities for a given user utterance in your model so that its text translates into machine-understandable formats, such as APIs and parameters.
The system uses an inference API to train NLU algorithms by using sample record data to identify intents and entities that are strong candidates for accurate prediction.
## NLU model consumption
Other ServiceNow® applications consume NLU model output, such as Virtual Agent.
For example, Virtual Agent administrators can configure a Virtual Agent Designer conversation flow to consume NLU models so that agent chatbots can better understand user statements in the conversation. For more information on how Virtual Agent consumes NLU models, see: [Natural Language Understanding \(NLU\) topic discovery in Virtual Agent](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/brazil/markdown/conversational-interfaces/va-NLU.md).
## Get started
<table id="table_lhx_jch_czb" class="nav-card"><tbody><tr><td>
[Explore\[Omitted image "bus-explore.svg"\] Alt text:Learn about NLU concepts and features.](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/brazil/markdown/intelligent-experiences/nlu-service/nlu-explore.md)
</td><td>
[Use\[Omitted image "bus-sdlc.svg"\] Alt text:Create, test, translate, and publish your NLU models.](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/brazil/markdown/intelligent-experiences/nlu-service/nlu-models.md)
</td></tr><tr><td>
[Integrate\[Omitted image "bus-integration-and-apis.svg"\] Alt text:Learn how Virtual Agent administrators can update NLU models from within Virtual Agent Designer.](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/brazil/markdown/intelligent-experiences/nlu-service/virtual-agent-nlu-model-builder-integration.md)
</td><td>
[Reference\[Omitted image "bus-learn.svg"\] Alt text:Learn about using models in different languages for use in other applications](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/brazil/markdown/intelligent-experiences/nlu-service/nlu-language-support.md)
</td></tr></tbody>
</table>## Troubleshoot and get help
- [Virtual Agent & NLU community page](https://www.servicenow.com/community/virtual-agent-nlu/ct-p/virtual-agent-natural-language)
- [Search the Known Error Portal for known error articles](https://support.servicenow.com/kb?id=kb_article_view&sysparm_article=KB0597477)
- [Contact Customer Service and Support](https://support.servicenow.com/now?draw=case)
| title | \(Legacy\) Natural Language Understanding |
| description | ServiceNow Natural Language Understanding \(NLU\) provides an NLU Workbench and an NLU inference service that you can use to enable the system to learn and respond to human-expressed intent. By entering natural language examples into the system, you help it understand word meanings and contexts so it can infer user or system actions. |
| locale | en-US |
| canonical_url | https://www.servicenow.com/docs/r/intelligent-experiences/nlu-service/nlu-landing.html |
| release | brazil |
| product | NLU Service |
| classification | nlu-service |
| topic_type | reference |
| last_updated | 2026-09-10 |
| reading_time_minutes | 5 |
| breadcrumb | Machine learning and natural language capabilitiesEnable AI Experiences |