|sf-intelligence|의 개요¶
|sf-intelligence|를 사용하여 조직 내 데이터를 기반으로 인사이트를 확보하고 조치를 취합니다. |sf-intelligence|를 사용하면 다음을 수행할 수 있습니다.
자연어를 사용하여 차트를 만들고 즉각적인 답변을 얻습니다. 기술적 전문 지식 없이도 사용자 지정 대시보드를 기다릴 필요 없이 추세를 발견하고 데이터를 분석할 수 있습니다.
정형 데이터와 비정형 데이터가 함께 포함된 수천 개의 데이터 소스를 액세스하고 분석합니다. 스프레드시트, 문서, 이미지, 데이터베이스의 인사이트를 동시에 연결할 수 있습니다.
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 AI Functions, Cortex Analyst, and Cortex Search.
다음 섹션을 사용하여 |sf-intelligence|를 설정하고 데이터 활용을 시작합니다. |sf-intelligence|에 대한 빠른 시작 가이드를 보려면 `Snowflake Intelligence 시작하기<https://quickstarts.snowflake.com/guide/getting-started-with-snowflake-intelligence/index.html>`_ 섹션을 참조하세요.
지원되는 모델 및 지역¶
|sf-intelligence|는 다음 모델을 지원합니다. 계정에 해당 모델에 대한 액세스 권한이 있는 한 이러한 모델을 사용할 수 있습니다. 자세한 내용은 모델 액세스 제어 섹션을 참조하십시오.
Claude 4.5
Claude 4.0
Claude 3.7
Claude 3.5
GPT 5
GPT 4.1
목록에 있는 모델은 모든 리전<label-cortex_llm_availability>`에서 제공되지 않을 수 있지만, Cortex 리전 간 추론을 사용하여 모든 클라우드 또는 리전에서 |sf-intelligence|를 사용할 수 있습니다. 여기에는 클라우드 및 모델이 제공되지 않는 리전도 포함됩니다. Cortex 리전 간 추론 구성에 대한 자세한 내용은 :doc:/user-guide/snowflake-cortex/cross-region-inference` 섹션을 참조하세요.
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_usto use Claude 4 and get the best performance. Without Cortex Cross-region inference, you are restricted to using Claude 3.5 inaws_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.
Snowflake Intelligence 설정하기¶
To set up Snowflake Intelligence for your users, do the following:
참고
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.
Snowsight 에 로그인합니다.
탐색 메뉴에서 AI & ML » Agents 를 선택합니다.
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;
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>;
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>;
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>;
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;
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 액세스 제어 요구 사항.
중요
기본적으로 |sf-intelligence|는 사용자의 기본 역할과 기본 웨어하우스를 사용합니다. |sf-intelligence|를 사용하도록 다른 사용자를 초대할 때는 해당 사용자가 기본 역할과 웨어하우스를 설정했는지 확인합니다.
참고
|sf-intelligence|의 모든 쿼리는 사용자의 자격 증명을 사용합니다. 사용자와 연관된 모든 역할 기반 액세스 제어 및 데이터 마스킹 정책은 에이전트와의 모든 상호 작용 및 대화에도 자동으로 적용됩니다.
에이전트 생성하기¶
To get started, create an agent that users can interact with in Snowflake Intelligence. For information about creating an agent, see Create an agent. For best practices when creating an agent, see Best Practices to Building Cortex Agents.
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;
참고
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>;
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>;
참고
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.AGENTSschema exists with one or more agents, users see agents from theSNOWFLAKE_INTELLIGENCE.AGENTSschema. 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.AGENTSschema 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¶
중요
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.AGENTSschema 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 Snowflake Intelligence 설정하기.
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>;
You can rename or drop the SNOWFLAKE_INTELLIGENCE database or AGENTS schema after the migration. For more information, see ALTER SCHEMA.
비공개 연결로 Snowflake Intelligence 구성¶
|sf-intelligence|는 AWS Privatelink와 Azure Private Link와의 통합을 지원하여 가상 사설 클라우드(VPC) 또는 가상 네트워크(VNet)와 |sf-intelligence| 간에 비공개 연결을 설정합니다. 비공개 연결을 구성하려면 올바른 DNS 확인 설정으로 이 비공개 연결을 통해 Snowflake Intelligence 서비스로 트래픽을 전달해야 합니다.
AWS PrivateLink 및 Azure Private Link는 Snowflake에서 제공하는 서비스가 아닙니다. 이들은 각각 Snowflake가 Snowflake 계정과 함께 사용하도록 지원하는 AWS 서비스 및 Microsoft 서비스입니다.
전제 조건¶
비공개 연결을 사용하여 |sf-intelligence|에 연결하기 전에 다음 전제 조건을 완료합니다.
/user-guide/admin-security-privatelink`의 지침을 따라 AWS PrivateLink를 설정하거나 :doc:/user-guide/privatelink-azure`의 지침을 따라 Azure Private Link를 설정하세요.
ACCOUNTADMIN 시스템 역할을 통해 SYSTEM$GET_PRIVATELINK_CONFIG 함수를 호출하여 :code: `regionless-snowsight-privatelink-url`이 제공되도록 보장합니다.
|sf-intelligence|에 연결¶
Snowflake Intelligence가 하위 도메인을 사용하도록 DNS를 구성하여 |sf-intelligence|에 연결합니다.
VPC 또는 VNET 엔드포인트의 DNS 이름에 다음 URL을 매핑하는 비공개 DNS 존 :code:`privatelink.snowflakecomputing.com`에 CNAME 레코드를 생성합니다.
si-<org-acct>.privatelink.snowflakecomputing.com
구성이 완료되면 네트워크 내 사용자는 다음 URL로 이동하여 |sf-intelligence|에 액세스할 수 있습니다.
https://si-<org-acct>.privatelink.snowflakecomputing.com
이 연결은 비공개 연결을 통해 안전하게 라우팅됩니다.
비공개 연결을 사용한 사용자 인증¶
비공개 연결을 사용하여 |sf-intelligence|에 액세스하는 사용자는 표준 Snowflake 인증 프로세스를 사용하며, 이를 위해서는 로그인 페이지에서 계정 식별자, 사용자 이름, 비밀번호를 제공해야 합니다.
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 관리형 MCP 서버.
Update Snowflake Intelligence settings¶
You can modify settings for the Snowflake Intelligence interface that users interact with Cortex Agents through.
Snowsight 에 로그인합니다.
탐색 메뉴에서 AI & ML » Agents 를 선택합니다.
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.
Save 를 선택합니다.
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.
Save 를 선택합니다.
문제 해결하기¶
table / search service / stage does not exist 오류가 발생하면 권한 문제가 있을 수 있습니다. 다음 권한이 올바르게 설정되었는지 확인합니다.
각 의미 체계 모델의 경우:
사용자의 기본 역할에는 의미 체계 모델 스테이지 또는 뷰의 데이터베이스 및 스키마, 그리고 테이블에 대한 USAGE 권한이 부여됩니다.
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.
사용자의 기본 역할에는 의미 체계 모델 또는 뷰에 정의된 각 테이블에 대한 SELECT 권한이 부여됩니다.
각 Cortex Search Service의 경우:
사용자의 기본 역할에는 Cortex Search Service의 데이터베이스 및 스키마에 대한 USAGE 권한이 부여됩니다.
사용자에게는 Cortex Search Service에 대한 USAGE 권한이 부여됩니다.
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 및 ML.