This collaboration brings generative and agentic AI capabilities directly to enterprise data, enabling joint customers to build and deploy AI-powered applications faster and more securely.
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Multi-year strategic agreement expands co-investment in customer success, workload migration, and go-to-market as Snowflake’s AWS Marketplace lifetime revenue exceeds $7 billion
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Snowflake will spend $6 billion on Graviton compute and AI over five years on AWS, reflecting the accelerating demand for data and AI workloads.
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Customers like Fetch and Hex deploy AI applications on data managed using Snowflake on AWS
MENLO PARK, CA — May 27, 2026 — Snowflake (NYSE: SNOW), an AI Data Cloud company, today announced that it has entered into a multi-year Strategic Alliance Agreement (SCA) with Amazon Web Services (AWS) to accelerate the adoption of enterprise agent AI and help joint customers around the world build and deploy AI faster and more securely. As part of the expanded collaboration, Snowflake is making its largest $6 billion multi-year infrastructure commitment to AWS to date, reflecting accelerating enterprise demand for AI and data workloads running on AWS.
Snowflake was founded on AWS 11 years ago, and its foundation has grown into one of the broadest and deepest collaborations in enterprise software. Today, the majority of Snowflake customers run on AWS, and AWS recognizes Snowflake as a key partner driving global customer adoption. The latest agreements build on this momentum with deeper product integration across generative and agent AI, expanded go-to-market through AWS Marketplace, customer success programs designed to help companies move from AI experimentation to production-scale outcomes, workload migration, and joint investments in strategic industry solutions.
“AI has generated a lot of excitement, but the real challenge and opportunity for companies is turning intelligence into action,” said Snowflake CEO Sridhar Ramaswamy. “We are moving into the age of the agent-based enterprise, where AI systems go beyond answering questions to helping organizations infer trusted data, orchestrate workflows, and drive real business outcomes. AWS makes it easy for enterprises to deploy AI directly into their managed data, enabling them to act faster, operate with greater clarity, and create measurable impact at scale.”
“Enterprises are rapidly moving from experimenting with AI to operating intelligent agents that drive real business outcomes,” said AWS CEO Matt Garman. “Snowflake has been built on AWS since its inception, and our deepening commitment to running on Graviton delivers the world-class performance, flexibility, and cost savings our customers need to run data warehousing and AI workloads at scale.”
Deploy AI where enterprise data resides
AI is only as powerful as the data behind it. Enhanced collaboration is rooted in a technology architecture that deploys underlying models directly into managed enterprise data, eliminating the complexity and risk of moving sensitive information between systems.
Snowflake Cortex AI allows customers to build and deploy AI applications for text-to-SQL conversion, summarization, sentiment analysis, and entity extraction directly within the Snowflake environment. Enterprises are rapidly adopting these capabilities to run AI on trusted, controlled data without moving data outside of secure boundaries. Snowflake leverages AWS Graviton processors, delivering significant price-performance improvements to customers, and leverages Amazon EC2 instances with high-performance GPU acceleration for AI model training and inference.
Accelerate AI adoption with AWS
Since Snowflake was first made available on AWS Marketplace, customers have adopted it as the fastest path to procure and deploy Snowflake’s AI and data capabilities, generating over $7 billion in lifetime sales. over $2 billion Calendar year 2025 sales will represent more than double the volume growth compared to the previous year. The expanded SCA will build on that trajectory and expand our joint initiatives to help more customers discover, source, and deploy AI and data solutions through AWS Marketplace. Simplify contracts and speed up procurement.
Snowflake also continues to expand its global footprint on AWS, with launches completed or underway in 10 new regions, including New Zealand (Auckland), South Africa (Cape Town), Thailand (Bangkok), AWS Europe Sovereign Cloud, and more, helping customers meet their data residency requirements and deploy AI closer to where they operate their businesses.
Customers deploying AI on governed data From startups to global enterprises, customers including Fetch and Hex use Snowflake on AWS to unify data, eliminate silos, and deploy AI applications and agents on managed data to drive measurable business impact.
“AI is deeply embedded in how we build and operate Fetch every day, and our collaboration with Snowflake and AWS strengthens that foundation,” said Daniel Block, general manager of revenue and partnerships at Fetch. “Using Snowflake Cortex AI, we’ve deployed a semantic agent that allows our sales teams to query campaign data in natural language and gain instant insights. This enables us to make faster, more informed decisions across our business and deliver more value to our brand partners.”
“Snowflake on AWS is the foundation that many of our customers rely on to process data faster,” said Caitlin Colgrove, co-founder and CTO of Hex. “For teams using Hex to explore, analyze, and build AI, having that layer be secure, managed, and performant is not just a nice-to-have; it’s what makes enterprise AI adoption a reality.”
Snowflake and AWS further demonstrate their shared vision for enterprise AI at Snowflake Summit 26.
Learn more about the power of Snowflake on AWS..
Forward-looking statements This press release contains express and implied forward-looking statements, including statements regarding Snowflake’s business strategies, plans, opportunities or priorities. Snowflake products, services, and technology offerings, including those that are in development or not generally available. Market growth, trends and competitive considerations. Snowflake’s vision, strategy, and expected benefits related to AI and other emerging product areas; and the integration, interoperability, and availability of Snowflake products, services, and technologies on third-party platforms. These forward-looking statements are subject to a number of risks, uncertainties and assumptions, including those described under the heading “Risk Factors” and elsewhere in Snowflake’s Quarterly Reports on Form 10-Q and Annual Reports on Form 10-K filed with the Securities and Exchange Commission. Given these risks, uncertainties and assumptions, actual results may differ materially and adversely from those anticipated or implied by the forward-looking statements. Therefore, forward-looking statements should not be relied upon as predictions of future events.
