Overview of Snowflake Intelligence¶

Use Snowflake Intelligence to gain insights and take action based on data in your organization. With Snowflake Intelligence, you can:

Create charts and get instant answers using natural language. You can discover trends and analyze data without technical expertise or waiting for custom dashboards.
Access and analyze thousands of data sources, including structured and unstructured data together. You can connect insights from spreadsheets, documents, images, and databases simultaneously.

Snowflake Intelligence uses agents, which are AI models that are connected to one or more semantic views, semantic models, Cortex search services, and tools. Agents can answer questions, provide insights, and show visualizations. Snowflake Intelligence is powered by Cortex AISQL, Cortex Analyst, and Cortex Search.

Use the following sections to set up Snowflake Intelligence and start using it to get value from your data. For a Quickstart guide about Snowflake Intelligence, see Getting Started with Snowflake Intelligence.

Supported models and regions¶

Snowflake Intelligence supports the following models. You can use these models as long as the account has access to them. For more information, see Control model access.

Claude 4.5
Claude 4.0
Claude 3.7
Claude 3.5
GPT 5
GPT 4.1

While the listed models may not be available in all regions, you can use Snowflake Intelligence in any cloud or region by using Cortex Cross-region inference. This includes clouds and regions where the models are not available. For more information about configuring Cortex Cross-region inference, see Cross-region inference.

When creating an agent, we recommend selecting Auto for the model. This lets Snowflake Intelligence automatically select the highest quality model for your account and automatically improves as new models become available.

AWS US - In AWS, Claude 4+ offers the highest quality and best speed performance. We recommend that you set up Cortex Cross-region inference for aws_us to use Claude 4 and get the best performance. Without Cortex Cross-region inference, you are restricted to using Claude 3.5 in aws_us.
Azure US - If you are using Snowflake Intelligence in East US, you can use GPT 4.1+ without Cortex Cross-region inference. Other region and model combinations require Cortex Cross-region inference setup for azure_us.
AWS EU - You can use Claude 4+ in this region as long as you configure Cortex Cross-region inference for aws_eu.
AWS APJ - You can use Claude 4+ in this region as long as you configure Cortex Cross-region inference for aws_apj.

Set Up Snowflake Intelligence¶

To set up Snowflake Intelligence for your users, do the following:

Note

The ACCOUNTADMIN role is the only role that has the CREATE SNOWFLAKE INTELLIGENCE ON ACCOUNT privilege required to create a Snowflake Intelligence object.

Create a Snowflake Intelligence object. The Snowflake Intelligence object is a single object meant to manage all agents used with Snowflake Intelligence in your account. You can only have one Snowflake Intelligence object in your account.
Add agents to the Snowflake Intelligence object.
GRANT USAGE privileges to the Snowflake Intelligence object.

Create a Snowflake Intelligence object¶

You can either use the Snowflake Intelligence UI or SQL to create a Snowflake Intelligence object.

Snowflake automatically creates the Snowflake Intelligence object when you modify the Snowflake Intelligence settings for the first time. When created using the UI, the Snowflake Intelligence object is named SNOWFLAKE_INTELLIGENCE_OBJECT_DEFAULT. You can’t specify a different name.

Sign in to Snowsight.

In the navigation menu, select AI & ML » Agents.

Select the Snowflake Intelligence tab.

Select Open settings. The Snowflake Intelligence object is created automatically if it doesn’t already exist. You can then add agents to the object.
To create a Snowflake Intelligence object, you can use the following command:
CREATE SNOWFLAKE INTELLIGENCE SNOWFLAKE_INTELLIGENCE_OBJECT_DEFAULT;
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Add agents¶

The Snowflake Intelligence object is an account-level object that contains a list of agents. You can add or remove agents from this object to create a curated list of agents for your users. For more information about adding or removing agents, see Configure the visibility of agents in Snowflake Intelligence.

Grant Snowflake Intelligence privileges¶

The following privileges control access to Snowflake Intelligence objects:

CREATE SNOWFLAKE INTELLIGENCE ON ACCOUNT: Account-level privilege that allows creating a Snowflake Intelligence object. This privilege is granted to ACCOUNTADMIN by default.

To grant this privilege to another role, run the following command:
```
GRANT CREATE SNOWFLAKE INTELLIGENCE ON ACCOUNT TO ROLE <role_name>;
```
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USAGE: Object-level privilege that allows users to view the list of agents added to the Snowflake Intelligence object and see configuration values.

To grant this privilege, run the following command:
```
GRANT USAGE ON SNOWFLAKE INTELLIGENCE SNOWFLAKE_INTELLIGENCE_OBJECT_DEFAULT TO ROLE <role_name>;
```
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ALTER: Object-level privilege that allows users to add or remove agents from the Snowflake Intelligence object and change configuration values. Account administrators have this privilege by default.

To grant this privilege, run the following command:
```
GRANT MODIFY ON SNOWFLAKE INTELLIGENCE SNOWFLAKE_INTELLIGENCE_OBJECT_DEFAULT TO ROLE <role_name>;
```
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To make the Snowflake Intelligence object visible to all of your users, grant USAGE privileges on the object to the PUBLIC role:

GRANT USAGE ON SNOWFLAKE INTELLIGENCE SNOWFLAKE_INTELLIGENCE_OBJECT_DEFAULT TO ROLE PUBLIC;

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As an ADMIN, you also have ALTER privileges on the Snowflake Intelligence object. This allows you to add or remove agents from the object to create a curated list of agents for your users.

To set up Snowflake Intelligence for your users, you must configure agent privileges. For information about the privileges required for agents, see Access control requirements.

Important

By default, Snowflake Intelligence uses the default role and the default warehouse of the user. When you invite others to use Snowflake Intelligence, make sure they’ve set a default role and warehouse.

Note

All of the queries from Snowflake Intelligence use the user’s credentials. All role-based access control and data-masking policies associated with the user automatically apply to all interactions and conversations with the agent.

Create an agent¶

To get started, create an agent that users can interact with in Snowflake Intelligence. For information about creating an agent, see Create an agent.

Configure the visibility of agents in Snowflake Intelligence¶

If you haven’t created a Snowflake Intelligence object and added agents to it, users see all agents they have access to in your account.

For the optimal experience, create a curated list of agents by adding them to the Snowflake Intelligence object. This allows you to control which agents appear in the Snowflake Intelligence interface for all users.

To see whether the Snowflake Intelligence object has been created in your account, use the following command:

SHOW SNOWFLAKE INTELLIGENCES;

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Note

Only one Snowflake Intelligence object can exist in an account.

Managing agents with the Snowflake Intelligence object¶

To add agents to the Snowflake Intelligence object, use the following command:

ALTER SNOWFLAKE INTELLIGENCE SNOWFLAKE_INTELLIGENCE_OBJECT_DEFAULT ADD AGENT <db.schema.agent_name>;

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To remove agents from the Snowflake Intelligence object, use the following command:

ALTER SNOWFLAKE INTELLIGENCE SNOWFLAKE_INTELLIGENCE_OBJECT_DEFAULT DROP AGENT <db.schema.agent_name>;

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Note

Any user or admin with the right database and schema privileges can create agents. However, agents are not automatically added to the Snowflake Intelligence object. Users must have the ALTER privilege on the Snowflake Intelligence object and USAGE privileges on the agent to add an agent to the Snowflake Intelligence object.

Administrators must have the USAGE privilege on the agent to add it to the Snowflake Intelligence object.

Agent visibility logic¶

Snowflake Intelligence uses the following logic to determine which agents are visible to users:

If the Snowflake Intelligence object exists and contains one or more agents, users see the individual agents from this curated list that they have access.
If the Snowflake Intelligence object exists but contains zero agents AND the SNOWFLAKE_INTELLIGENCE.AGENTS schema exists with one or more agents, users see agents from the SNOWFLAKE_INTELLIGENCE.AGENTS schema. This ensures that Snowflake Intelligence doesn’t break if you haven’t migrated your agents yet.
If the Snowflake Intelligence object doesn’t exist or contains zero agents AND the SNOWFLAKE_INTELLIGENCE.AGENTS schema doesn’t exist or contains zero agents, users see all agents that they have access to in the account.

Migrating from the deprecated SNOWFLAKE_INTELLIGENCE.AGENTS schema¶

Important

The SNOWFLAKE_INTELLIGENCE.AGENTS schema is deprecated. If you’re currently using this schema, we recommend migrating to the Snowflake Intelligence object.

If you’re using the SNOWFLAKE_INTELLIGENCE.AGENTS schema, your agents will continue to work. However, migrating to the Snowflake Intelligence object provides the following benefits:

Flexibility: Create and manage agents anywhere in your account without needing to centralize them in a single schema.

Improved permission management: Separate the ability to create agents from the ability to publish them in Snowflake Intelligence.

Avoid naming conflicts: Eliminate potential conflicts with the SNOWFLAKE_INTELLIGENCE.AGENTS schema name.

Easier agent visibility management: Use a single object to control which agents appear to all users.

Make sure you’ve created a Snowflake Intelligence object before you migrate your agents. For information about creating a Snowflake Intelligence object, see Set Up Snowflake Intelligence.

After you’ve created an object, use the following code to add an agent to the Snowflake Intelligence object:

ALTER SNOWFLAKE INTELLIGENCE SNOWFLAKE_INTELLIGENCE_OBJECT_DEFAULT ADD AGENT SNOWFLAKE_INTELLIGENCE.AGENTS.<agent_name>;

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You can rename or drop the SNOWFLAKE_INTELLIGENCE database or AGENTS schema after the migration. For more information, see ALTER SCHEMA.

Configure Snowflake Intelligence with private connectivity¶

Snowflake Intelligence supports integration with AWS Privatelink and Azure Private Link to establish a private connection between your Virtual Private Cloud (VPC) or virtual network (VNet) and Snowflake Intelligence. Configuring private connectivity requires setting up the correct DNS resolution to direct traffic to the Snowflake Intelligence service through this private connection.

Note that AWS PrivateLink and Azure Private Link are not services provided by Snowflake. They are an AWS service and Microsoft service, respectively, that Snowflake supports to use with your Snowflake account.

Prerequisites¶

Complete the following prerequisites before connecting to Snowflake Intelligence with private connectivity.

Set up AWS PrivateLink by following the instructions in AWS PrivateLink and Snowflake or Azure Private Link by following the instructions in Azure Private Link and Snowflake.
Ensure that a :code: regionless-snowsight-privatelink-url is available by calling the SYSTEM$GET_PRIVATELINK_CONFIG function using the ACCOUNTADMIN system role.

Important

Snowflake Intelligence exclusively uses the regionless URL format for private connectivity access. Unlike other private connectivity URLs used for Snowflake, you should not include a region identifier, such as us-west-2, in the hostname. Any attempts to connect using a region-specific URL will result in a failure.

Connect to Snowflake Intelligence¶

Connect to Snowflake Intelligence by configuring the DNS for Snowflake Intelligence to use the subdomain.

Create a CNAME record in your private DNS zone, privatelink.snowflakecomputing.com, that maps the following URL to the DNS name of your VPC or VNET endpoint.
```
si-<org-acct>.privatelink.snowflakecomputing.com
```
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After the configuration is complete, users within your network can access Snowflake Intelligence by navigating to the following URL:

https://si-<org-acct>.privatelink.snowflakecomputing.com

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The connection is routed securely over the private connection.

User authentication with private connectivity¶

Users accessing Snowflake Intelligence with private connectivity use the standard Snowflake authentication process, which requires them to provide their account identifier, username, and password on the login page.

Use the Snowflake-managed MCP server to connect to your agents¶

Any agent that you create in Snowflake, or the tools that the agent is connected to, can have a managed endpoint for other systems to connect with MCP. This provides a seamless integration layer for tools like Claude Desktop, Langgraph, and other tools that integrate with MCP.

The MCP server provides a standards-based interface that allows AI agents to discover and invoke tools, such as Cortex Analyst and Cortex Search, and retrieve the data they need. For more information, see Snowflake-managed MCP server.

Update Snowflake Intelligence settings¶

You can modify settings for the Snowflake Intelligence interface that users interact with Cortex Agents through.

Sign in to Snowsight.
In the navigation menu, select AI & ML » Agents.
Select the Snowflake Intelligence tab.
Select Open settings.
From the General settings section, you can modify the following settings:
- Brand display name: The name of the Snowflake Intelligence interface that is displayed to users.
- Welcome message: The message that is displayed when users first open the Snowflake Intelligence interface.
- Primary domain: The domain that users use to access Snowflake Intelligence.
Select Save.
From the Custom appearance section, you can modify the following settings:
- Color theme: The color theme of the Snowflake Intelligence interface. You can provide a custom primary color in hexadecimal format.
- Full-length logo and Compact logo: The logos that are displayed when the navigation pane is expanded or collapsed, respectively.
- Favicon: The icon that is displayed in the browser tab.
Select Save.

Troubleshooting¶

If you encounter table / search service / stage does not exist errors, there might be privilege issues. Verify that the following privileges are set correctly:

For each semantic model:
- The user’s default role is granted USAGE on the database and schema of the semantic model stage or view, and table.
- If using the older semantic model, the user’s default role is granted READ on the stage that stores the semantic model file.
- If using a semantic view, the user’s default role is granted REFERENCES on the semantic view.
- The user’s default role is granted SELECT for each table defined in the semantic model or view.
For each Cortex search service:
- The user’s default role is granted USAGE on the database and schema of the Cortex search service.
- The user is granted USAGE on the Cortex search service.

Legal notices¶

Where your configuration of Snowflake Intelligence uses a model provided on the Model and Service Flow-down Terms, your use of that model is further subject to the terms for that model on that page.

The data classification of inputs and outputs are as set forth in the following table.

Input data classification	Output data classification	Designation
Usage Data	Customer Data	Covered AI Features [1]

For additional information, refer to Snowflake AI and ML.