Snowflake announced the research preview of Project SnowWork, a new autonomous enterprise AI platform designed to help business users massively accelerate workflows. Acting as a proactive AI partner, Project SnowWork empowers individuals and teams across the business to simply ask for what they need and have Project SnowWork securely complete multi-step tasks based on conversational prompts.
Whether it’s building a board-ready forecast slide deck, creating a spreadsheet that identifies churn risks, or uncovering supply chain bottlenecks, Project SnowWork autonomously executes simple or complex workflows end-to-end to drive action.
“We are entering the era of the agentic enterprise, ushering in a fundamentally new way to work. This shift is about much more than technology, it’s about unlocking new levels of productivity and efficiency by embedding intelligence directly into the operating fabric of the enterprise,” said Sridhar Ramaswamy, Chief Executive Officer, Snowflake. “Project SnowWork looks to put secure, data-grounded AI agents on every surface, so business leaders and operators can move from question to action instantly. By elevating AI from experimentation to enterprise-grade autonomous execution, Project SnowWork serves as the secure foundation for how modern enterprises will get work done in the AI era.”
The rise of the agentic enterprise is not just about answering questions with AI, rather, it’s a shift to using AI to drive decisions and action. This future will require enterprises to connect intelligence, applications, and enterprise data and context into a trusted foundation that can continuously coordinate action at scale.
Project SnowWork makes this possible by bringing Snowflake’s enterprise data platform and AI capabilities directly to business users through a simple, outcome-driven desktop experience. More than a productivity agent, Project SnowWork can:
- Plan and autonomously execute simple or complex multi-step workflows across governed Snowflake data to deliver finished outputs — from reprioritising sales territories to executive-ready presentations.
- Generate analysis with recommended actions, turning insights into prioritised next steps tailored to each business role.
- Securely orchestrate data, AI, and enterprise systems to complete tasks end-to-end, reducing backlogs and accelerating decisions.
Unlike general-purpose AI agents, Project SnowWork is built on a single enterprise-wide source of truth with governed metrics, shared business definitions, cross-cloud interoperability, and built-in security and auditability.
Key capabilities Project SnowWork delivers:
- Pre-built, persona-specific skills: Provides pre-configured, role-aware AI “profiles” for finance, sales, marketing, operations, and more that understand common business workflows, terminology, and KPIs, accelerating time-to-value.
- Multi-step task completion: Enables the AI platform to autonomously plan and complete complex workflows — querying data, applying analysis, synthesising insights, generating structured deliverables, and preparing next steps within a single interaction — compressing reporting cycles and eliminating manual coordination across systems.
- Built-in security and access controls: Automatically enforces Snowflake’s role-based access controls (RBAC), masking policies, audit logging, and data governance rules — ensuring AI actions operate within the same trusted perimeter as enterprise data.
“Enterprises have invested heavily in data platforms and AI, yet the last mile of translating governed data into everyday business outcomes remains largely manual,” said Sanjeev Mohan, Principal at SanjMo. “Project SnowWork represents a meaningful shift from AI as an analytical tool to AI as an execution layer embedded directly into enterprise workflows. By grounding autonomous task execution in trusted, governed Snowflake data, shared business definitions, and cross-cloud and cross-domain interoperability, the company is extending its platform from a system of insight to a system of action, which is where measurable business value is ultimately realised.”
AI built for action, not just insights
Organisations have invested heavily in modern data platforms and AI, yet most business users still rely on analysts, static dashboards, and siloed systems to answer basic questions. Today’s AI tools often require technical expertise and lack the enterprise data foundation needed to deliver trusted, actionable outcomes.
The result is a widening gap between AI’s potential and its real business impact. Project SnowWork closes that gap by securely embedding AI into the flow of work, enabling every employee to operate with the speed, precision, and insight once reserved for data specialists.
It allows business users to move from intent to actions and outcomes without filing tickets with data teams or searching for static dashboards. For example, Sales Operations teams can now automate repetitive reporting, work across multiple data sources without coding, and generate presentation-ready deliverables in minutes instead of days.
Advancing Snowflake’s enterprise AI architecture
Snowflake’s portfolio of AI products enables every employee to use AI on trusted, governed data so organisations can embrace the agentic enterprise where intelligence drives secure, data-driven action across the business.
For business users, Snowflake Intelligence is the enterprise intelligence agent built to turn all the knowledge within an organisation into trusted business insights. It enables every employee to ask complex questions in natural language and move beyond the “what” to uncover the critical “why.” Grounded in governed enterprise data and shared business context, it delivers transparent, verifiable answers inside Snowflake’s secure perimeter. Project SnowWork extends this idea by helping teams act on those insights and execute multi-step workflows directly on top of trusted Snowflake data. For builders who want to turn complex data engineering, analytics, machine learning, and agent-building tasks into simple, informed interactions, Cortex Code is a data-native AI coding agent that automates and accelerates end-to-end enterprise development. It generates production-ready code, orchestrates workflows, and enforces best practices, enabling teams to move from prototype to deployment with speed and confidence.
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