Snowflake has been evolving quickly over the least year with it’s Cortex AI offering. Snowflake CoCo is Cortex Copilot. It’s one of the clearest examples of Snowflake embracing a modern co-pilot approach that works incredibly well. They embraced several functions that I cover in my anatomy of a modern copilot article.
Instead of exporting data into external AI tools or building complicated integrations, you can now interact with your Snowflake data using natural language. The AI assistant lives directly inside the platform and works against the data already stored in your warehouse.
What Cortex Copilot Actually Does
At its core, Cortex Copilot provides a natural language interface to Snowflake. The formal Snowflake CoCo documentation covers what is supported, and I admit I haven’t read it! I jump in, ask logical questions for real production problems and I get correct answers 90%+ of the time.
Off the top of my head, here are the tasks I have successfully tested CoCo that felt frictionless.
- Validating queries multiple versions of queries
- Setting up a new DBT project
- Migrating views and materialized views to DBT models
- Troubleshooting broken SQL
- Granting permissions and RBS auditing tasks
- Reviewing and troubleshooting YML for semantic models
- Advanced searching based on table / view structure
- Text to SQL
- SQL diff comparison
- Validating results between queries
Why This Matters for Data Teams
Most companies have invested heavily in building modern data stacks. Data warehouses, pipelines, and analytics tools are already in place. The pace of innovation from Snowflake has moved at a rate that is impossible to keep up with. Cortex provides a level playing field where new features, documentation, and best practices for using Snowflake, DBT, and other integrations has been packaged up as skills by the Snowflake team.
AI Where the Data Already Lives
One of the biggest advantages of Snowflake Cortex Copilot is aware of schema , semantic models, administrative functions and more. As modern co-pilot it enforces role based permissions and access policies. That has has been a breath of fresh air as I invite more information workers into Snowflake Workspaces. That was something that I never would have imagined starting 2026!.
How to Enable Snowflake Cortex in Snowflake
Getting started with Cortex requires only a couple of account level configuration changes.
First, enable the Cortex analyst functionality.
ALTER ACCOUNT SET ENABLE_CORTEX_ANALYST = TRUE;Next, allow access to the models that power the Cortex features.
ALTER ACCOUNT SET CORTEX_ENABLED_CROSS_REGION = 'ANY_REGION';Some organizations prefer to restrict model access to a specific region. In that case the configuration can be set more narrowly.
ALTER ACCOUNT SET CORTEX_ENABLED_CROSS_REGION = 'AWS_US';Once these settings are enabled, Cortex capabilities become available within the Snowflake platform.
Final Thoughts on Snowflake CoCo
Cortex Copilot represents a meaningful shift in how we can interact with Snowflake.
I have already wired up Snowflake Cortex Copilot CLI to work inside of Cursor. It’s not as fast, but the additional layer of planning, orchestration and micro-knowledge loops has transformed the way I work. I don’t use Claude Code, but I am sure it works the same there. If you want my template, feel free to contact me directly.
The barrier to entry to work with data is the lowest it has ever been with Snowflake CoCo! Happy coding.
