Snowflake, the company specializing in the AI Data Cloud, has announced the launch in research preview phase of Project SnowWork, a new autonomous enterprise artificial intelligence platform designed to significantly streamline workflows.
conceived as a proactive AI assistant, Project SnowWork allows professionals and teams across the organization to easily request tasks through conversational instructions, with the platform handling the execution securely, even when involving multiple steps.
Whether it’s preparing a forecast presentation for the board, generating a spreadsheet to detect churn risks in purchase processes, or identifying bottlenecks in the supply chain, Project SnowWork is capable of autonomously carrying out both simple and complex tasks, completing end-to-end processes to enhance operational efficiency.
“We are entering the era of the enterprise agentic, marking the beginning of a fundamentally new way of working. This shift goes far beyond technology; it’s about unlocking new levels of productivity and efficiency by embedding intelligence directly into the fabric of the business operations,” says Sridhar Ramaswamy, CEO of Snowflake. “Project SnowWork aims to put secure, data-driven AI agents at every point of contact or interface, so business leaders and operators can go instantly from asking a question to taking action. By moving AI from experimentation to autonomous enterprise-grade execution, Project SnowWork lays the secure foundation for how modern businesses will operate in the AI era.”
The rise of the enterprise agentic is not just about answering questions with AI but involves a shift toward using AI to drive decisions and actions. This future will require companies to connect intelligence, applications, data, and business context into a trustworthy foundation capable of coordinating actions continuously at scale.
Project SnowWork makes this possible by bringing Snowflake’s enterprise data platform and AI capabilities directly to business users through a straightforward, results-oriented desktop experience. More than a productivity agent, Project SnowWork can:
- Autonomously plan and execute multi-step workflows, simple or complex, using governed Snowflake data to deliver outcomes—from adjusting priorities in business areas to creating executive presentations.
- Generate insights with recommended actions, transforming knowledge into prioritized next steps tailored to each role within the organization.
- Securely orchestrate data, AI, and enterprise systems, completing tasks from start to finish, reducing delays and speeding up decision-making.
Unlike general-purpose AI agents, Project SnowWork relies on a single source of truth at the enterprise level with governed metrics, shared business definitions, cloud interoperability, and integrated security and auditability.
Key capabilities offered by Project SnowWork include:
- Predefined skills tailored to each individual: Provides role-aware, preconfigured AI “profiles” for finance, sales, marketing, operations, and others that understand common business workflows, terminology, and KPIs, accelerating value realization.
- End-to-end task completion: Enables the AI platform to plan and autonomously complete complex workflows (querying data, applying analyses, synthesizing insights, generating structured deliverables, and preparing next steps within a single interaction), compressing reporting cycles and eliminating manual coordination between systems.
- Built-in security and access controls: Automatically applies 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.
“Organizations have invested heavily in data and AI platforms, but the ‘last mile’ of translating governed data into everyday business outcomes remains largely manual,” says Sanjeev Mohan, Principal at SanjMo. “Project SnowWork represents a significant shift from AI as an analytical tool to AI as an execution layer directly integrated into business workflows. By basing autonomous task execution on trusted, governed Snowflake data, shared business definitions, and cross-cloud interoperability, the company is evolving its platform from a knowledge system to an execution system—where measurable business value is finally realized.”
AI designed for execution, not just insight
Organizations have invested heavily in modern data platforms and AI; however, most business users still rely on analysts, static dashboards, and fragmented systems to answer basic questions. Current AI tools often require technical expertise and lack the enterprise data foundation needed to deliver reliable, actionable results.
This creates an increasing gap between the potential of AI and its actual business impact. Project SnowWork bridges that gap by securely integrating AI into workflows, enabling each employee to operate with the speed, accuracy, and insight once reserved for data specialists.
It allows business users to move from intent to action and results without opening tickets to coordinate with data teams or searching for static dashboards. For example, Sales Operations teams can now automate repetitive reporting, work with multiple data sources without coding, and generate presentation-ready deliverables in minutes instead of days.
Evolving Snowflake’s enterprise AI architecture
Snowflake’s AI product portfolio enables every employee to leverage AI over trusted, governed data, helping organizations adopt an enterprise agentic approach where intelligence drives safe, data-driven actions across the business.
For business users, Snowflake Intelligence is the enterprise intelligence agent designed to turn all organizational knowledge into reliable business insights. It empowers each employee to ask complex questions in natural language and go beyond the “what” to uncover the critical “why.” Built on governed enterprise data and shared business context, it provides transparent, verifiable answers within Snowflake’s secure perimeter. Project SnowWork extends this capability by helping teams act on these insights and run multi-step workflows directly on trusted Snowflake data.
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