---
sourceDocument: Yokohama Enable AI
sourceDocumentLink: https://servicenow-prod.fluidtopics.net/r/yokohama/intelligent-experiences

 Release :

    - yokohama

ft:locale :

    - en-US

ft:publication_title :

    - Yokohama Enable AI

ft:clusterId :

    - platai

bundleId :

    - platai

workflow :

    - Platform


---

# Model management

# Model management {#ariaid-title1}

Release version: Yokohama  
Updated January 30, 2025  
![](https://www.servicenow.com/docs/portal-asset/ico-clock) 3 minutes to read
Summarize  
![AI sparkle icon](https://servicenow.com/docs/portal-asset/ai-sparkle-icon) Summarized using AI  
This content was generated using new OpenAI-powered functionality. Results are provided on an as is basis and are not guaranteed to be accurate or complete.  

## Summary of Model management

The Model management feature in the NLU Workbench allows you to effectively oversee the entire life cycle of your Natural Language Understanding (NLU) models.
It supports an iterative process of building, testing, publishing, and tuning models tailored for applications like Virtual Agent, AI Search, and Issue Auto Resolution.
The available phases and functionalities adapt based on the chosen model application.
Show full answer Show less  
To utilize these phases, ensure you have the necessary NLU plugins installed, including the NLU Workbench - Advanced Features and Intent Discovery, which are available from the ServiceNow Store and required for model testing and performance monitoring.

## Creating and Building Models

Create NLU models via the NLU Workbench under the appropriate application tab (Virtual Agent or AI Search). You can start from a prebuilt model, import training data via CSV, or build a model from scratch. Once created, build your model by adding and managing:

* **Intents:** Define user requests the model can understand.
* **Entities:** Extract contextual details from user inputs.
* **Vocabulary:** Include business-specific terms and acronyms for better understanding.
* **Test set:** Add utterances and expected intents for validation.

Training the model with relevant utterances prepares it for real user interactions.

## Testing and Publishing Models

Test your model's performance to identify improvements using the NLU Workbench - Advanced Features. This testing phase helps ensure your model meets accuracy and confidence requirements. Once satisfied with the test results, publish the model to make it available for use by applications like Virtual Agent.

## Tuning Models

If the NLU Workbench - Advanced Features plugin is installed and your model is for Virtual Agent, you can use the Tune your model phase. This phase leverages the Expert Feedback Loop to incorporate real user utterances, continuously improving model accuracy. For Issue Auto Resolution models, tuning occurs through the IAR Tuning interface.

## Model Settings

Modify your model's name, description, and confidence threshold via the Settings page on the model overview. The confidence threshold controls how certain the model must be before predicting an intent, allowing you to fine-tune prediction sensitivity.

## Additional Features

**Irrelevance Detection:** This feature enables your NLU model to identify and avoid responding to utterances that are irrelevant, helping keep Virtual Agent conversations focused and accurate.  
Manage your NLU model's life cycle in the NLU Workbench. Model management phases guide you through the iterative process of
building, testing, and publishing your model.

Bringing your NLU model from creation to deployment requires multiple
steps, separated into phases. You can return to earlier phases when you want to adjust and
maintain your model.

The phases available for your model depend on the model's application.
The system will display a phase, button, or function only when it applies to your model's application.  
To use the model management phases, ensure you have all the necessary NLU plugins. For more information, see the following resources:

* [Activate the NLU Workbench](https://servicenow-prod.fluidtopics.net/GAg2cSeu9PvaEZsZbkZ5zg "Activate the following plugins to activate the NLU Workbench.")
* [Install NLU Workbench - Advanced Features](https://servicenow-prod.fluidtopics.net/e6w1em~rJVUJ6NXkr4vAbg "You can install the NLU Workbench - Advanced Features application (com.snc.nlu.workbench.advanced) if you have the admin role.")
* [Install Intent Discovery](https://servicenow-prod.fluidtopics.net/diJdbUSVIuId7YSFnN8Heg "You can install the Intent Discovery application (sn_nlu_discovery) if you have the admin role.")

{#model-management-phases__ul_rlr_mxr_yqb}  
Note:  
NLU Workbench - Advanced Features and Intent Discovery are available from the ServiceNow Store. NLU model testing and performance monitoring require NLU Workbench - Advanced Features.

## Create a model {#model-management-phases__section_ukd_2zc_dwb}

To create a model for Virtual Agent or AI Search, navigate to NLU WorkbenchModels. The Virtual Agent tab opens by default.
Select the appropriate tab for the model you want to create.  
You can choose different ways to create a model:

* Use prebuilt model: Copy one of the included read-only models, and add content specific to your business.
* Import data from CSV: Upload a CSV file that contains training utterances and matched intents.
* Start from blank: Go through the process of setting up a new model from scratch.
{#model-management-phases__ul_vrz_p3s_yqb}

To get started, see [Creating models](https://servicenow-prod.fluidtopics.net/c14X3QfDPWvrI_h_gvU6AA "Creating models is the first step to taking advantage of Natural Language Understanding (NLU) in your instances. Create models for Virtual Agent and AI Search in the NLU Workbench.").

## Model management phases {#model-management-phases__section_mm2_cbd_dwb}

After creating a model, access its management phases by navigating to NLU WorkbenchModels. Select the tab for your model's application, then the name of the model to open the Model details
page on the model overview.

There are three phases on a Virtual Agent model's overview page: Build and train your model, Test and
publish your model, and Tune your model. These phases guide you as you build and improve your
model.

## Build and train your model {#model-management-phases__section_dqv_gry_wqb}

Build the model by adding and managing content:

* Intents: Add more intents to broaden the range of user requests that your model can understand.
* Entities: Add more entities so that your model can extract more contextual details from your users' requests.
* Vocabulary: Add vocabulary to enable the model to better understand words and phrases that are specific to your business, such as industry terms and acronyms.
* Test set: Add test utterances and their expected intents to your model's default test set.

{#model-management-phases__ul_a2s_2wm_bwb}

To learn more, see [Build and train your model](https://servicenow-prod.fluidtopics.net/R96~pHdqkNQ2d1hnPjjHng "After creating a model, build the model's content by adding intents, entities, vocabulary, and test set utterances. Your NLU model content determines how the model responds to user inputs.").

Train your model
using utterances that the model is likely to encounter from your users. To learn more, see [Train and try your NLU model](https://servicenow-prod.fluidtopics.net/KRneHtgkkSp2DpurFaQdXw "Train and try your model iteratively so that its intents and entities are validated, compiled, and saved to your model.").

## Test and publish your model {#model-management-phases__section_bqb_pzz_xqb}

Test your model to gauge the performance and identify areas for improvement.  
Note:  
Model testing requires the NLU Workbench - Advanced Features store application. For more information, see [NLU Workbench - Advanced Features](https://servicenow-prod.fluidtopics.net/0JGgNSuhG9NPozaTxULmLw "NLU Workbench - Advanced Features expands the functionality of NLU Workbench to help you manage and improve your models.").

For more information on testing and thresholds, see [Test and publish your model](https://servicenow-prod.fluidtopics.net/DPaBLeE6TiKefL~QJbRX8Q "Assess the performance of your NLU model to identify areas for improvement. Then publish your model to make it available to other applications such as Virtual Agent.").

When you're satisfied with the results of testing, publish your model to make it available for
use by other applications. For more information, see [Publish your NLU model](https://servicenow-prod.fluidtopics.net/~qrDzWr0FQtpEuEXdn7B6g "Publish your Natural Language Understanding (NLU) model to activate it and make it available for use in other applications that consume NLU.").

## Tune your model {#model-management-phases__section_lcf_xym_bwb}

If NLU Workbench - Advanced Features is installed, and your model is created
for Virtual Agent, the Tune your model phase is enabled.
With this phase, you can use Expert Feedback Loop to incorporate actual
user utterances into your model.

For more information, see [Tune your model](https://servicenow-prod.fluidtopics.net/s8q0g0N_oWhhwmw6ab8qNA "On your model's overview in NLU Workbench, open the Tune your model phase to review and incorporate user utterances from the Expert Feedback Loop.").

If your model is created for Issue Auto Resolution, you will be taken to
IAR Tuning by selecting the name of your model in the
IAR tab of the NLU Workbench homepage. For more
information, see [Issue Auto Resolution Tuning in NLU](https://servicenow-prod.fluidtopics.net/yZnssYuKMoMIVH59K60Eeg "Use the NLU Workbench homepage to support Issue Auto Resolution (IAR) tuning in NLU.").

## Model settings {#model-management-phases__section_uhr_jwg_mrb}

Use the Settings page of the model overview to change the name and
description of the model. You can also modify the confidence threshold of the model. The
confidence threshold determines how confident the model must be to predict an intent.

For more information, see [NLU model settings](https://servicenow-prod.fluidtopics.net/9DCue~pqIqM_bEihwOdQIQ "Change your NLU model's name, description, or confidence threshold on the Settings page of the model overview.").
* **[Creating models](https://servicenow-prod.fluidtopics.net/c14X3QfDPWvrI_h_gvU6AA)**   
  Creating models is the first step to taking advantage of Natural Language Understanding (NLU) in your instances. Create models for Virtual Agent and AI Search in the NLU Workbench.
* **[Build and train your model](https://servicenow-prod.fluidtopics.net/R96~pHdqkNQ2d1hnPjjHng)**   
  After creating a model, build the model's content by adding intents, entities, vocabulary, and test set utterances. Your NLU model content determines how the model responds to user inputs.
* **[Test and publish your model](https://servicenow-prod.fluidtopics.net/DPaBLeE6TiKefL~QJbRX8Q)**   
  Assess the performance of your NLU model to identify areas for improvement. Then publish your model to make it available to other applications such as Virtual Agent.
* **[Irrelevance detection in NLU](https://servicenow-prod.fluidtopics.net/NwbaT5ofR5JghXSGZ~0gYg)**   
  Keep Virtual Agent chats focused with Irrelevance detection. Use the Irrelevance detection feature to train your NLU model to avoid making predictions for utterances that are not relevant.
* **[Tune your model](https://servicenow-prod.fluidtopics.net/s8q0g0N_oWhhwmw6ab8qNA)**   
  On your model's overview in NLU Workbench, open the Tune your model phase to review and incorporate user utterances from the Expert Feedback Loop.
* **[NLU model settings](https://servicenow-prod.fluidtopics.net/9DCue~pqIqM_bEihwOdQIQ)**   
  Change your NLU model's name, description, or confidence threshold on the Settings page of the model overview.

*[\>]: and then