Create a custom embedding model
Create your custom embedding model in the Generative AI Model Configuration table so that your AI Search RAG application can use it to generate embeddings for semantic indexing. This setup ensures the model is recognized and properly connected to send and receive requests.
Before you begin
You must create a connection and credential alias for your embedding model. For more information, see Create a Connection & Credential alias
Role required: admin
Procedure
-
Navigate to All, and then enter
sys_generative_ai_model_config.listin the filter to go to the Generative AI Model Configuration [sys_generative_ai_model_config] table. -
Select New.
-
On the form, fill in the fields.
-
Field
Description
Active
Option to activate the embedding model.
Model
A unique name for your embedding model.
Domain
Domain you want to associate the model with. For example, AI Search RAG.
External
Option to make this model available for external use.
Connection and Credential Alias
Connection and credential alias that you created on your own for the custom embedding model.
Supported Language
Languages supported for this model. By default, the supported language is English.
Model Type
The type of model used for a specific purpose. For example Embedding Model.
Vector Dimension
The value shouldn't exceed 4096.This field appears only if you have selected Embedding Model in the Model Type field.
Application
Name of the application this model is configured for.
Provider
Name of the Generative AI provider mapping.
Max Tokens
Maximum limit to generate embeddings.
Result
The new embedding model is created.
What to do next
Set a provider for an embedding model.
--- title: Create a custom embedding model description: Create your custom embedding model in the Generative AI Model Configuration table so that your AI Search RAG application can use it to generate embeddings for semantic indexing. This setup ensures the model is recognized and properly connected to send and receive requests. locale: en-US canonical_url: https://www.servicenow.com/docs/r/australia/platform-administration/ai-search/create-byom.html release: australia product: AI Search classification: ai-search topic_type: task last_updated: "2026-09-10" reading_time_minutes: 1 breadcrumb: [Configuring bring your own model \(BYOM\), Configuring your embedding model, AI Search RAG \(Retrieval-Augmented Generation\), Semantic index configuration for indexed sources, Indexed sources, Configure, AI Search, Search administration, Configure core features, Administer the ServiceNow AI Platform] --- # Create a custom embedding model Create your custom embedding model in the Generative AI Model Configuration table so that your AI Search RAG application can use it to generate embeddings for semantic indexing. This setup ensures the model is recognized and properly connected to send and receive requests. ## Before you begin You must create a connection and credential alias for your embedding model. For more information, see [Create a Connection & Credential alias](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/platform-security/connection-alias.md) Role required: admin ## Procedure 1. Navigate to **All**, and then enter `sys_generative_ai_model_config.list` in the filter to go to the Generative AI Model Configuration \[sys\_generative\_ai\_model\_config\] table. 2. Select **New**. 3. On the form, fill in the fields. 4. <table id="table_ynd_bjk_bgc"><thead><tr><th> Field </th><th> Description </th></tr></thead><tbody><tr><td> Active </td><td> Option to activate the embedding model. </td></tr><tr><td> Model </td><td> A unique name for your embedding model. </td></tr><tr><td> Domain </td><td> Domain you want to associate the model with. For example, AI Search RAG. </td></tr><tr><td> External </td><td> Option to make this model available for external use. </td></tr><tr><td> Connection and Credential Alias </td><td> Connection and credential alias that you created on your own for the custom embedding model. </td></tr><tr><td> Supported Language </td><td> Languages supported for this model. By default, the supported language is English. </td></tr><tr><td> Model Type </td><td> The type of model used for a specific purpose. For example Embedding Model. </td></tr><tr><td> Vector Dimension </td><td> The value shouldn't exceed 4096.This field appears only if you have selected `Embedding Model` in the **Model Type** field. </td></tr><tr><td> Application </td><td> Name of the application this model is configured for. </td></tr><tr><td> Provider </td><td> Name of the Generative AI provider mapping. </td></tr><tr><td> Max Tokens </td><td> Maximum limit to generate embeddings. </td></tr></tbody> </table>5. Select **Submit**. ## Result The new embedding model is created. ## What to do next Set a provider for an embedding model.
| title | Create a custom embedding model |
| description | Create your custom embedding model in the Generative AI Model Configuration table so that your AI Search RAG application can use it to generate embeddings for semantic indexing. This setup ensures the model is recognized and properly connected to send and receive requests. |
| locale | en-US |
| canonical_url | https://www.servicenow.com/docs/r/australia/platform-administration/ai-search/create-byom.html |
| release | australia |
| product | AI Search |
| classification | ai-search |
| topic_type | task |
| last_updated | 2026-09-10 |
| reading_time_minutes | 1 |
| breadcrumb | Configuring bring your own model \(BYOM\)Configuring your embedding modelAI Search RAG \(Retrieval-Augmented Generation\)Semantic index configuration for indexed sourcesIndexed sourcesConfigureAI SearchSearch administrationConfigure core featuresAdminister the ServiceNow AI Platform |