Deploy an autonomous AI platform as the control plane that connects enterprise data, intelligence, and action.
In furthering its “Agent Enterprise” vision, Snowflake has launched Project SnowWork, an autonomous enterprise AI platform that moves artificial intelligence from insight generation to real-world execution.
Currently in research preview for limited customers, Project SnowWork enables business users to perform complex multi-step workflows using conversational prompts.
This reduces reliance on manual coordination between teams, tools, and data systems.
The platform acts as a proactive AI partner, allowing users to request results such as building board presentations, identifying churn risks, and analyzing supply chain bottlenecks, and allowing the system to autonomously plan and execute tasks end-to-end.
“To effectively leverage agent technology, enterprises need more than just models and applications. They need a coordination layer, or central control plane, that coordinates intelligence, enterprise data, policy, and execution across the organization to facilitate agent cohesion,” said Snowflake CEO Sridhar Ramaswamy.
“Today, we introduced Project SnowWork, now available in research preview for some customers, and this is the first step in delivering this control plane and connecting enterprise data, intelligence, and action in a managed way for business users,” he added.
This marks a shift in enterprise AI, where systems are no longer limited to responding to queries or generating recommendations, but are expected to determine next steps and take action within defined enterprise policies and governance frameworks.
This helps address the last-mile gap between enterprise data and business execution.
Automate complex business workflows across enterprise systems
Despite investments in AI and modern data platforms, organizations still rely on analysts, static dashboards, and fragmented tools to turn insights into action.
According to the company, SnowWork addresses this issue by allowing users to go directly from intent to execution in a single action.
The platform autonomously adjusts workflows by querying enterprise data, generating analytics, integrating insights, and delivering final outputs with recommended next steps.
It also introduces persona-specific AI profiles personalized for functions such as finance, sales, marketing, and operations.
These profiles understand business context, workflows, and key performance indicators, allowing non-technical users to generate relevant and actionable output.
The system can create structured deliverables such as reports, spreadsheets, and presentations, reducing the time required for tasks that traditionally require days of cross-departmental coordination.
Snowflake positions this as a transition from “AI as copilot to AI as execution layer” embedded directly into enterprise workflows, enabling faster decision-making and reducing operational backlogs.
Building a control plane for agent enterprises
Project SnowWork’s key differentiator is its architecture, which Snowflake describes as a step toward building a control plane for the agent enterprise.
This control layer connects enterprise data, AI models, and business applications to ensure that AI-driven actions are coordinated, managed, and aligned with organizational policies.
Unlike general-purpose AI tools, SnowWork runs on Snowflake’s managed data foundation and uses shared business definitions, role-based access controls, audit logs, and data security policies to ensure that all actions are based on a single source of truth.
The platform evaluates the user’s intent and determines what actions should be performed, under what constraints, when human intervention is required, and how to coordinate execution across systems.
This enables enterprises to move from isolated AI use cases to integrated systems where intelligence drives secure, data-backed actions at scale.
Project SnowWork reflects a broader shift in enterprise computing from systems that process data to systems that reason and operate within defined boundaries.
It forms the foundation of the agentic enterprise, combining trusted data, AI models, enterprise systems, and control layers to drive coordinated actions.
Snowflake positions AI as the layer that connects intelligence and execution, turning AI into a system for action.
