Cloud data giant Snowflake has committed $6B to AWS through 2032, reflecting growing confidence in future demand for its platform. The deal is the latest example of how the biggest winners in the AI era may not be the companies building models, but the companies that enable enterprise data.
The agreement extends the two companies’ long standing partnership. It deepens the integration between Snowflake’s platform and AWS services. Among the planned initiatives are tighter connections with Amazon Bedrock and other AWS AI capabilities. The goal is to allow customers to access and build AI applications using data managed in Snowflake.
Snowflake and AWS said they will continue working together on tools and services designed to simplify AI deployment for joint customers.
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“Enterprises are rapidly moving from experimenting with AI to putting intelligent agents to work that drive real business outcomes,” said Matt Garman, CEO of AWS. “Snowflake has built on AWS since day one, and their deepened commitment to run on Graviton delivers the world-class performance, flexibility, and cost savings customers need to run data warehousing and AI workloads at scale.”
The timing of expanded partnership matches the recent momentum gained by Snowflake’s AI business. During its recent earnings report, the company raised its full year product revenue guidance. It also highlighted growing adoption of AI related products across its platform.
Snowflake shared that more than 5,200 customers are now using its weekly AI and machine learning capabilities. In addition, products such as Cortex AI, Cortex Agents, and Document AI are attracting increasing interest from organizations looking to build AI-powered applications on top of enterprise data.
Snowflake’s confidence also appears to be backed by strong spending trends from its customers. The company said Snowflake customers spending on AWS doubled to $2B in 2025 alone.
To provide some context to what this translates to – AWS says Snowflake has generated roughly $7B in sales through AWS Marketplace since its founding in 2012. This makes the new $6B infrastructure commitment notable both for its scale and for the growth it implies over the coming years.
Those offerings are designed to help customers move beyond simple chat interfaces. Cortex AI provides access to large language models and AI functions within Snowflake, while Cortex Agents enables organizations to build agents that can search, retrieve, and act on enterprise information. Document AI focuses on extracting and structuring information from unstructured content such as PDFs and business documents.
The expanded AWS relationship is intended to strengthen those capabilities. A major focus is deeper integration with Amazon Bedrock, AWS’s service for accessing foundation models from multiple providers. By connecting Snowflake more closely with Bedrock, customers can use different models while continuing to work with data already stored and governed within the Snowflake platform.
For enterprises, that reduces the need to move large volumes of data into separate AI environments. Instead, organizations can build applications and agents closer to where their data already resides while maintaining existing security, governance, and compliance controls. The companies said they will continue developing tools and services aimed at simplifying AI deployment for joint customers.
A significant portion of Snowflake’s commitment could support AWS Graviton processors, Amazon’s in house chip technology. While Nvidia’s GPUs remain central to AI training and inference, the growth of AI applications and agents is also increasing demand for the broader infrastructure required to process, move, store, and manage data.
AWS has positioned Graviton as a lower cost alternative for many cloud workloads, making it an increasingly important part of the company’s AI infrastructure strategy. Snowflake’s $6B commitment represents another high profile endorsement of that approach.
AWS’s custom chip strategy appears to be gaining traction lately. Meta recently agreed to deploy tens of millions of AWS Graviton cores as part of a multibillion dollar AI infrastructure partnership, while AWS has said its custom silicon business, which includes Graviton and Trainium processors, has reached a $20B annual revenue run rate.
For Snowflake, the agreement is a vote of confidence that enterprise demand for its offerings will continue to grow in the years ahead. For AWS, this deal represents another large commitment from a major customer at a time when cloud providers are increasingly competing to capture the infrastructure spending generated by the AI boom. Together, the deal reflects how both data platforms and cloud providers are emerging as key beneficiaries of enterprise AI adoption.
The post Snowflake’s $6B AWS Bet Signals Where Enterprise AI Spending Is Headed Next appeared first on BigDATAwire.
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Author: Ali Azhar
