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Snowflake targets 'agentic enterprise' with unified control plane for AI and data - SiliconANGLE
Snowflake targets 'agentic enterprise' with unified control plane for AI and data Snowflake Inc. is expanding its push into enterprise artificial intelligence with a set of updates to its Snowflake Intelligence and Cortex Code offerings, positioning its platform as a centralized control layer for what it calls the "agentic enterprise." The data cloud company said the enhancements are designed to help organizations move beyond AI experimentation toward production use by integrating data, models and enterprise applications into a single governed environment. The updates are part of a broader industry shift from AI systems that generate responses to those that can take action across business workflows. Snowflake Intelligence (pictured) functions as a context-aware AI agent for business users. The company said the updated system can automate routine tasks, perform multi-step analysis and connect to commonly used enterprise applications through new integrations based on the Model Context Protocol. Supported services include Google LLC's Gmail, Google Calendar and Google Docs, Atlassian Corp. PBC's Jira and Salesforce Inc.'s namesake customer relationship management suite and Slack. An iPhone application, which enters public preview soon, extends those capabilities to smartphones, allowing users to query data and trigger workflows remotely. Additional features include "deep research," which generates multi-step, cited reports, and "artifacts," which enable users to save and share analyses and workflows. Snowflake said the system continuously learns from user behavior to personalize outputs and automate recurring tasks over time while keeping results grounded in governed enterprise data. Cortex Code, an AI coding agent designed for data-centric workflows, is being expanded to be a builder layer for AI. Since its launch in late 2025, Snowflake said more than half of its customers are using the tool to accelerate development workflows. New capabilities extend Cortex Code across external data systems including Amazon Web Services Inc.'s Glue, Databricks Inc.'s platform and the open-source PostgreSQL, allowing developers to build applications without migrating data. The platform also integrates with other AI systems through MCP and the Agent Communication Protocol, enabling interoperability with existing agent frameworks. Snowflake is also introducing integrations with popular environments such as Visual Studio Code and a plugin for Anthropic PBC's Claude Code. A new software development kit supporting Python and TypeScript allows enterprises to embed Cortex Code capabilities into applications written in those languages. Additional features include browser-based "sandboxes" for running code without local setup, along with tools that allow developers to preview workflows before execution and interact directly with charts and tables. Snowflake said more than 9,100 customers are now using its AI products weekly, citing examples of enterprises applying the technology to operational analytics, customer service and manufacturing. Executives framed the updates as part of a broader effort to simplify how organizations deploy AI at scale. "AI is changing how every company operates, and the platforms that win will make it easy to put AI into practice with the right data and guardrails," Baris Gultekin, vice president of AI at Snowflake, said in a statement. The company's strategy centers on consolidating data, governance and AI capabilities into a unified platform, an approach it argues helps enterprises manage the complexity of multi-system environments while accelerating the transition from pilot projects to production deployments.
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Snowflake Expands Snowflake Intelligence and Cortex Code to Power Agentic Enterprise Control Plane
Snowflake announced significant updates across Snowflake Intelligence and Cortex Code, advancing its vision to become the control plane for the agentic enterprise. Snowflake announced significant updates across Snowflake Intelligence and Cortex Code, advancing its vision to become the control plane for the agentic enterprise. As AI systems evolve from answering questions to taking action, these enhancements enable organizations to connect even more data sources, enterprise systems, and AI models with their trusted Snowflake data within a unified experience. This allows enterprises to align their data, tools, and workflows with AI agents built on Snowflake -- enabling more seamless action on data that reflects how their business actually runs.
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Snowflake announced major updates to Snowflake Intelligence and Cortex Code, positioning its platform as a unified control plane for the agentic enterprise. The enhancements help organizations move AI from experimentation to production by integrating data sources, models, and enterprise applications into a single governed environment with over 9,100 customers now using its AI products weekly.
Snowflake is expanding its enterprise AI capabilities with significant updates to Snowflake Intelligence and Cortex Code, positioning the data cloud platform as a centralized control plane for organizations deploying AI agents across business workflows
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. The enhancements arrive as the industry shifts from AI systems that simply generate responses to those capable of taking action across complex operational environments. By integrating data sources, models, and enterprise applications into a single governed environment, Snowflake aims to help organizations transition from AI experimentation to production deployments at scale2
.Snowflake Intelligence now functions as a context-aware AI agent designed for business users, capable of automating routine tasks and performing multi-step analysis while staying grounded in governed enterprise data
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Source: SiliconANGLE
The updated system connects to commonly used enterprise applications through new integrations based on the Model Context Protocol, supporting services including Gmail, Google Calendar, Google Docs, Atlassian's Jira, and Salesforce's CRM suite and Slack. An iPhone application entering public preview extends these capabilities to smartphones, allowing users to query data and trigger business workflows remotely. Additional features include "deep research" for generating multi-step, cited reports, and "artifacts" that enable users to save and share analyses. The system continuously learns from user behavior to personalize outputs and automate recurring tasks over time
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.Cortex Code, an AI coding agent for data-centric workflows, is being expanded to serve as a builder layer for enterprise AI. Since launching in late 2025, more than half of Snowflake customers have adopted the tool to accelerate development workflows
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Source: DT
New capabilities extend Cortex Code across external data systems including AWS Glue, Databricks' platform, and PostgreSQL, allowing developers to build applications without migrating data. The platform integrates with other AI systems through the Model Context Protocol and Agent Communication Protocol, enabling interoperability with existing agent frameworks. Snowflake is introducing integrations with popular developer tools such as 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 capabilities into applications. Additional features include browser-based sandboxes for running code without local setup and tools for previewing workflows before execution
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.Related Stories
Snowflake reports that more than 9,100 customers now use its AI products weekly, with enterprises applying the technology to operational analytics, customer service, and manufacturing use cases
1
. "AI is changing how every company operates, and the platforms that win will make it easy to put AI into practice with the right data and guardrails," said Baris Gultekin, vice president of AI at Snowflake. The company's strategy centers on consolidating data, governance, and AI capabilities into a unified control plane, an approach designed to help enterprises manage the complexity of multi-system environments while accelerating production deployments1
. As AI agents become more capable of taking action rather than simply answering questions, these updates enable organizations to connect data sources, enterprise systems, and AI models within a unified experience, aligning tools and workflows with how businesses actually operate2
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