Snowflake Inc. is enhancing its enterprise artificial intelligence capabilities with updates to Snowflake Intelligence and Cortex Code. The company aims to position its platform as a central control layer for what it terms the "agentic enterprise." These updates are designed to move organizations from AI experimentation to production by unifying data, models, and enterprise applications in a single, governed environment.
Snowflake Intelligence now functions as a context-aware AI agent for business users, automating routine tasks and performing multi-step analysis. New integrations, based on the Model Context Protocol, connect the system to applications like Google Workspace, Jira, Salesforce, and Slack. An upcoming iPhone application will allow users to query data and trigger workflows remotely. Features such as "deep research" for generating cited reports and "artifacts" for saving and sharing analyses are also included. The system learns from user behavior to personalize outputs and automate tasks, while ensuring results are based on governed enterprise data.
Cortex Code, an AI coding agent, is expanding its role as a builder layer for AI. Since its launch, it has been used by over half of Snowflake's customers to accelerate development. New capabilities allow Cortex Code to work with external data systems including Amazon Web Services Glue, Databricks, and PostgreSQL, enabling developers to build applications without data migration. The platform also integrates with other AI systems through MCP and the Agent Communication Protocol for interoperability.
Snowflake is also introducing integrations with Visual Studio Code and a plugin for Anthropic's Claude Code. A new software development kit supporting Python and TypeScript allows enterprises to embed Cortex Code into their applications. Browser-based "sandboxes" for running code and tools for previewing workflows are also part of the update.
More than 9,100 customers are now using Snowflake's AI products weekly, with applications in operational analytics, customer service, and manufacturing. Executives emphasize that these updates simplify AI deployment at scale, enabling companies to easily implement AI with the right data and safeguards. Snowflake's strategy focuses on consolidating data, governance, and AI capabilities into one platform to manage complexity and speed up production deployments.