Snowflake commits $6B to AWS for Graviton CPUs as AI infrastructure spending accelerates

In more good news for Amazon, Snowflake signs $6B deal with AWS for AI CPU chips | TechCrunch

Cloud data storage giant Snowflake has signed a new $6 billion five-year agreement with the cloud provider, the companies announced on Wednesday. Snowflake has always run on Amazon Web Services -- though obviously, these days, it is also available on Microsoft Azure and Google Cloud. For comparison on just how big this deal is for these companies, Snowflake has sold $7 billion worth of its services via AWS Marketplace total since it was founded in 2012, AWS says. So it's contracting to spend on AWS equal to almost all the money it has ever brought in from that cloud. It can do that because Snowflake's customers are accelerating their spending on AWS as of late, Snowflake says, doubling their spending in 2025 to $2 billion for that calendar year. What's driving the growth is, naturally, AI. Snowflake has been offering its AI building tool, Cortex AI, for a couple of years now. It's a tool that makes sense: Snowflake is where much of an enterprise's data lives. The AI tool can provide features like a text interface for database queries (just ask, in regular language), summary reports, and so on. Of particular note is that Snowflake is signing this contract for more access to AWS's home-grown ARM-based CPU chip, Graviton. As AI moves from training to daily usage to automation via agents, CPU usage skyrockets. While GPUs handle training and reasoning, CPUs handle most of the rest of the tasks associated with AI, particularly agents. Amazon CEO Andy Jassy last month boasted that Amazon's own homegrown AI chips offer "better price-performance" than Nvidia's offerings, though AWS still uses Nvidia's chips in its cloud. Demand is so high for AI processing that hyperscalers like AWS are deploying them as fast as they can. On top of that, all of the major AI model makers (and many other AI offerings) have architected their apps specifically for Nvidia's chips. Still, Amazon's own chips are a more affordable option for the cloud giant to deploy. Amazon, ever the price-conscious company, says it passes those savings along to its customers. Consequently, these chips are luring in new multi-billion-dollar deals. Last month, for instance, AWS signed a deal to provide millions of Graviton chips to Meta for its growing AI compute needs. That was a big win for AWS because Meta had signed a $10 billion deal with Google Cloud a few months earlier. More than that, these deals are serving as notice to Nvidia that competitive CPUs from the cloud giants are attempting to come for its lunch. Google has also been making its own AI chips for years. Microsoft just launched its Maia AI chip in January. Not surprisingly, Nvidia CEO Jensen Huang said last week that he's more than ready to defend, and even grow, his turf. The new AI-specific CPU his company has developed, called Vera, represents a 'brand new" $200 billion market for Nvidia, he proclaimed after delivering another record-breaking quarter last week. And he's already sold $20 billion worth, he said. While Nvidia may not be giving up market share to Amazon or any cloud provider that easily, AWS's multi-billion-dollar cloud deals show how AI is lifting its boat. Whichever companies benefit most from the rise of AI in our work and home lives, the cloud providers are getting their share.

Snowflake to burn $6B on AWS Graviton CPUs and AI accelerators

Cloud data warehouse Snowflake plans to spend $6 billion on Amazon's custom Graviton CPUs and AI accelerators over the next five years. The collab aims to reduce friction in connecting Snowflake customer data with a growing number of AI services built atop AWS' cloud infrastructure. "We are making it easier for enterprises to bring AI directly to governed data, so they can move faster, operate with greater density and create measurable impact at scale," Snowflake CEO Sridhar Ramaswamy said in a canned statement. Snowflake is a long-time AWS customer, having built the company atop the cloud titan's servers going back to 2011. Over the past few years, Snowflake has shifted an increasing amount of compute from Intel and AMD CPUs to Amazon's own Arm-based Graviton instances. Now in their fifth generation, Amazon's latest Graviton processors cram 192 Arm Neoverse V3 cores which are fed by 12 channels of memory up to 8800 MT/s. As we've previously reported, CPUs are back in the spotlight again after years of being overshadowed by GPUs and other AI accelerators. The models themselves still run on GPUs, but the tools and functions those models call -- a SQL query or Python script, for example -- do not. Those workloads still rely on CPUs. This has driven renewed demand for CPU cores as each agent's performance is inherently limited by how quickly the processor can service the request. Under the agreement, Snowflake will run and train its GenAI models and services using a combination of GPUs running in AWS and Graviton CPU cores. For example, Snowflake says that its Cortex AI platform can convert natural language to SQL queries, summarize data, and conduct sentiment analysis. According to Amazon, Snowflake's lifetime AWS marketplace sales crossed $7 billion and exceeded $2 billion during the 2025 calendar year. Clearly the data warehousing platform is betting these AI tools will continue to drive revenues enough to justify splashing $1.2 billion a year on additional infrastructure. Gamble or not, Wall Street doesn't seem to worried, with Snowflake rallying by more than 30 percent in after hours trading Wednesday. Snowflake isn't the only company diving deeper into Graviton's orbit. Back in April, Meta revealed plans to deploy tens of millions of Amazon's Graviton 5 CPU cores. The multi-year collaboration was expected to make the social network one of the biggest consumers of AWS' homegrown silicon. Much like Snowflake's $6 billion investment in Amazon's infrastructure, Meta's cloud spend is largely aimed at securing cores for AI agents. But unlike Snowflake, which for better or worse remains heavily reliant on AWS for compute, Meta's tie up may only be a stopgap while it awaits Arm's buzzword-packed AGI CPUs. ®

Snowflake soars 25% on earnings beat and plan to spend $6 billion on Amazon cloud

Amazon CEO Andy Jassy appears at a company event in New York on Feb. 26, 2025. Amazon said Wednesday that its cloud division has landed a $6 billion spending commitment from Snowflake, which includes the use of the company's custom silicon and chips for artificial intelligence. Snowflake's purchase of services and technology from Amazon Web Services will occur over five years, according to a press release about the agreement. Snowflake intends to expand its use of Amazon's Graviton general-purpose chips, as well as cloud-based graphics processing units for AI. It's the latest sign that AWS is gaining momentum in AI as clients turn to the market-leading cloud for more advanced technologies. In April, Claude creator Anthropic said it aims to spend over $100 billion on AWS over a decade. Amazon also has a deal with OpenAI. Both of its agreements with the AI model companies include an equity investment, while the Snowlfake deal does not. Snowflake, which went public in 2020, has a market cap of just over $60 billion, and has long relied on AWS. Snowflake rose 25% in extended trading after it announced financial results. The company reported 39 cents in adjusted earnings per share on $1.39 billion in revenue. Analysts polled by LSEG had expected 32 cents per share and $1.32 billion in revenue. At the time of Snowflake's IPO, it disclosed an amended deal with an unnamed cloud provider for $1.2 billion in spending over five years, with $350 million coming in the final year. The provider was Amazon, a Snowflake spokesperson told CNBC. In 2023, the agreement climbed to $2.5 billion. The new $6 billion arrangement implies an average annual spend of $1.2 billion.

Snowflake commits $6bn to AWS over five years, with Graviton chips at the centre

The five-year commitment is 2.4x larger than Snowflake's 2023 AWS deal and lands as shares jump 38% on a Q1 earnings beat. The Graviton component is the part that matters strategically. Snowflake has signed a five-year, $6bn commitment to Amazon Web Services in what both companies are framing as the largest expansion of their 11-year relationship to date. The agreement, announced on Tuesday, includes commitments to run on AWS Graviton, the cloud provider's custom Arm-based CPU line, and to develop deeper product integrations for what Snowflake is now describing as "agentic enterprise" workloads. The trajectory of Snowflake's AWS spending is the part that frames the size of the announcement. The company committed $1.2bn at its 2020 IPO. That figure rose to $2.5bn in a 2023 renewal. The new $6bn agreement is roughly five times the 2020 commitment and 2.4 times the 2023 one. The expansion mirrors Snowflake's own growth: the company posted Q1 fiscal-2027 earnings on Wednesday that beat estimates substantially, and the stock jumped roughly 38% on the combined earnings and AWS-deal news. The Graviton component is the part worth pausing on. AWS Graviton, now in its fourth generation, is Amazon's in-house Arm-server processor line, designed to replace x86 chips from Intel and AMD inside AWS data centres at substantially better price-performance. Snowflake committing to run its data-cloud workloads on Graviton at scale is a meaningful endorsement of the Arm-server thesis that has been quietly reshaping cloud-infrastructure economics for five years. It is also a useful Amazon-side data point against the backdrop of yesterday's news that ByteDance is building its own Arm and RISC-V CPUs to escape Intel and AMD pricing pressure. The migration to custom Arm-server silicon, hyperscaler-led, is now visibly the structural story in data-centre CPUs. For AWS specifically, the Snowflake deal lands inside a stretch of large AI-infrastructure commitments. Anthropic has committed to large AWS spending over multi-year terms; OpenAI signed a meaningful Microsoft Azure-competitor agreement on AWS earlier this year; Meta has been visibly expanding its AWS footprint for inference workloads. Snowflake is the latest in that sequence and the largest non-foundation-model commitment on the list. AWS's capacity to absorb $6bn of additional five-year demand against an already-stretched data-centre pipeline is itself a useful indicator of how rapidly Amazon is bringing new capacity online. The strategic context for Snowflake is the agentic-AI thesis the company has been visibly betting on. Snowflake's pitch, like that of every enterprise-data-platform vendor at scale right now, is that AI agents will operate primarily over the trusted, governed enterprise data already inside customers' cloud-warehouse environments, rather than over external training corpora. Building that future requires substantially more compute integration with the underlying cloud provider; it requires direct access to AWS's native AI primitives (Bedrock, SageMaker, the Q assistant) and deeper marketplace and go-to-market integration. The remaining open question is the Databricks comparison. Snowflake's most visible competitor is more directly bundled with Azure (through its 2023 Microsoft partnership) and has been positioning aggressively on multi-cloud agnosticism. Snowflake's deeper AWS commitment, including the explicit Graviton anchor, signals a different strategic bet: pick the larger hyperscaler partner, lock in customer-acquisition flow through AWS Marketplace, and accept the implicit single-cloud tilt that comes with it. Whether that pays off against Databricks's diversification posture is the multi-year question. AWS Marketplace sales for Snowflake doubled year-on-year to $2bn in 2025, which suggests the integration logic is already working commercially. Neither company disclosed which specific Graviton generation Snowflake is committing to. Snowflake CEO Sridhar Ramaswamy said the company will publish more detail at the AWS re:Invent conference later this year.

Snowflake commits $6B to Amazon Web Services over 5 years in latest AI infrastructure deal

Snowflake on Wednesday committed to spend $6 billion on Amazon Web Services over five years, adding to the cloud giant's growing roster of AI infrastructure deals. Snowflake, which sells cloud-based data warehousing and AI tools to big businesses, said the commitment includes the use of Amazon's custom Graviton processors and other chips to power AI and agentic applications. The deal expands a relationship that dates back to the data company's founding 11 years ago. Snowflake's five-year AWS spending commitment has grown from $1.2 billion at the time of its IPO in 2020 to $2.5 billion in 2023 to the current $6 billion, CNBC reported. It's the latest in a series of large-scale commitments for AI-related infrastructure on AWS, including deals of more than $100 billion with Anthropic, $138 billion with OpenAI, accompanying Amazon's investments in the AI labs. Meta also plans to deploy tens of millions of Graviton chip cores for agentic AI. Amazon's custom chips business has become a major revenue driver. Amazon CEO Andy Jassy said in his annual shareholder letter in April that the business generates more than $20 billion a year and is growing at triple-digit rates. Two large customers asked to buy all of Amazon's available Graviton capacity for 2026, Jassy wrote in the letter at the time, and the company was compelled to turn them down. Snowflake is headquartered in Bozeman, Mont., with a large presence in the Bay Area and a significant office in Bellevue, Wash. The company reported strong fiscal first-quarter results Wednesday, with revenue of $1.39 billion, beating analyst expectations. Its stock rose as much as 33% in extended trading.

Snowflake's stock surges after-hours on solid earnings beat and multibillion-dollar AWS cloud deal - SiliconANGLE

Snowflake's stock surges after-hours on solid earnings beat and multibillion-dollar AWS cloud deal Snowflake Inc.'s shares shot up in late trading today after it announced a $6 billion spending commitment on Amazon Web Services Inc.'s cloud infrastructure, including a deal to use the company's custom artificial intelligence chips. The cloud database giant also reported stellar first-quarter earnings results, powering past Wall Street's targets in a sign that the AI boom is providing it with a real tailwind, contrary to many investor's fears. The company's purchase of AWS's cloud technology and services will span the next five years. It includes a commitment by Snowflake to use more of Amazon's general-purpose Graviton chips, as well as its custom AI accelerators. For AWS, the deal underlines the increasing momentum it's gaining in the AI industry, as an increasing number of businesses turn to its trusted cloud platform to run more sophisticated "agentic" AI workloads. It follows an announcement by Claude chatbot creator Anthropic PBC last month, which revealed it will spend $100 billion on AWS infrastructure over the next decade. AWS has also struck a multibillion-dollar deal with the rival AI firm OpenAI Group PBC. The deals with Anthropic and OpenAI include equity investments, but Snowflake is a more mature and publicly traded company, and so that's not the case in today's deal. Snowflake, which went public back in 2020, boasts a market capitalization of more than $60 billion, and has long relied on Amazon's cloud services. Snowflake's latest financial results were compelling. The cloud data giant reported earnings before certain costs such as stock compensation of 39 cents per share, cruising past the Street's target of 32 cents. Meanwhile, its revenue soared by 33% from a year ago to $1.39 billion, surpassing the $1.32 billion consensus estimate by a solid margin. Snowflake's guidance was strong too. The company called for an adjusted operating margin of 12.5% and between $1.415 billion and $1.42 billion in second quarter product revenue. Wall Street is looking for a margin of just 11.9% on product revenue of $1.37 billion. The company also raised its full-year revenue guidance. It's now looking for total product revenue of approximately $5.84 billion, up from an earlier call for $5.66 billion. That puts it well ahead of the analyst's target of $5.67 billion. According to Snowflake Chief Executive Sridhar Ramaswamy (pictured), the company decided to raise its guidance as a result of the "strong momentum" it is seeing both in its core business and in AI. "AI continues to be a powerful tailwind for Snowflake, and Q1 marks a clear inflection point in that journey," he said. "With Cortex Code and Snowflake Intelligence, we are extending from the trusted foundation for enterprise data and context to become the control plane for the Agentic Enterprise. We are seeing strong momentum from both AI-driven acceleration of our core platform and growing adoption of our first-party AI products, positioning Snowflake to lead in this new era." The report comes in the wake of a rough few months for software companies, during which investors have become increasingly concerned that AI startups could be about to cause some major disruption to the old way of doing things in the enterprise. Many are convinced that AI agents, which can complete tasks based on a simple, plain language prompt, will completely reshape the way business gets done. One of the main fears is that enterprises will simply use coding agents to build customized versions of the software they currently pay hefty subscription fees for. In an earnings call earlier this month, executives of Palantir Technologies Inc. claimed to have done this, replacing their customer relationship management platform with an agentic-built system. Agents may also pose problems for software firm's business models. As they become more numerous on corporate networks, that's going to clash with the per-user fee structure that many software companies operate, forcing them to switch to consumption-based pricing instead. However, Snowflake already does this, charging its customers based on the amount of storage and compute resources they use, though its gross margins are generally quite a bit lower than software firms that run on user-based pricing models. With Snowflake's cloud data warehouse, companies pool all of their data from multiple different sources into one centralized repository, where it can serve as a clean and governed source of truth for enterprise data analytics and forecasting. Snowflake has long argued that its software won't be replaced by AI, but instead will actually become invaluable for it, acting as a hub that enables autonomous agents to work more reliably. After all, agents are no different to human workers in that they still need a way to access cleaned and governed enterprise data. Where they do differ is that they can work much faster, which could increase consumption of Snowflake's cloud and boost its bottom line. The company also develops its own AI agents, and they are the reason behind its acquisition of a startup called Natoma, which was also announced today. Natoma is an enterprise-grade Model Context Protocol platform for AI agents, and its technology will enable Snowflake to build a natively integrated governance and identity layer for AI agents that require MCP tool access. Using this layer, enterprises will be able to securely connect AI agents to third-party databases, APIs and software platforms, the company explained. Investors were extremely encouraged by what they saw, and Snowflake's stock gained more than 36% in late trading, helping to erase much of the losses it has suffered this year. However, Snowflake still has a way to go, for its stock is still down 20% in the year to date, while the broader S&P 500 Index has gained 10% over the same timeframe.

Snowflake boosts forecast, signs $6 billion AWS deal as enterprise AI adoption grows

Snowflake has boosted its annual product revenue forecast. This rise is driven by increased enterprise spending on AI applications. Companies are moving more data tasks to Snowflake's cloud platform. This positive development sent Snowflake's shares soaring. A significant five-year deal with Amazon Web Services further strengthens their partnership, focusing on enterprise AI. Snowflake raised annual product revenue forecast on Wednesday, as enterprises ramped up spending on AI applications and shifted more data workloads to its cloud platform, sending its shares surging 36% in extended trading. The company also signed a five-year deal worth $6 billion with Amazon Web Services ⁠to use ⁠AWS' Graviton processors and AI infrastructure, as their partnership deepens around enterprise AI. The latest deal will include deeper product integrations around generative and agentic AI, expanded go-to-market efforts through AWS Marketplace and workload migrations aimed at helping businesses move from experimenting with AI projects to using them routinely. "The new deal with Amazon ⁠adds another element to the growth path for Snowflake," said Gil Luria, managing director of D.A. Davidson. "It allows Snowflake to ⁠take an even bigger role in their customers transition to AI and aligns them even more with their biggest partner." Snowflake has benefited from surging enterprise demand for its core data warehousing products, with migrations from legacy systems and increased use of machine learning tools adding momentum. It has seen strong adoption of its tools such as Cortex Code and Snowpark. The company raised its product revenue forecast for fiscal 2027 to $5.84 billion, from $5.66 billion projected earlier. "Based on a combination of ⁠strength in our core data platform business and meaningful uplift from AI capabilities... we are increasing our FY27 outlook," CEO Sridhar Ramaswamy said on a post-earnings call. Snowflake expects second-quarter product revenue to be between $1.415 billion and $1.420 billion, compared with analysts' average estimate of $1.37 billion, according to data compiled by LSEG. Its first-quarter revenue came in at $1.39 billion, above the estimate of $1.32 billion.

Snowflake Strikes Expanded SCA Deal, $6B Infrastructure Commitment With AWS

Snowflake also announced an acquisition that will extend the company's data governance perimeter beyond the Snowflake platform to AI operations and interactions across an enterprise. AI and data cloud company Snowflake said today that it has signed a multi-year strategic collaboration agreement (SCA) with Amazon Web Services that the two companies said will accelerate enterprise agentic AI adoption and help customers build and deploy AI systems more quickly and securely. Snowflake said that under the SCA it is making a $6 billion, multi-year infrastructure commitment to AWS. Snowflake already runs its data and AI services on AWS, but the company said this is its largest commitment to date to AWS. Snowflake also disclosed that it has signed a definitive agreement to acquire Natoma, which develops an enterprise Model Context Protocol (MCP) platform for AI agents, in a bid to extend "Snowflake's governance perimeter from data assets to AI actions and interactions across the enterprise." [Related: Snowflake CEO: 'I'm Not In The Business of Selling AI. I'm In The Business Of Creating Value.'] The Wednesday announcements came as Snowflake announced its fiscal 2027 first quarter (ended April 30, 2026) financial results. The company reported that revenue in the quarter was $1.39 billion, up more than 33 percent from $1.04 billion one year earlier. "AI continues to be a powerful tailwind for Snowflake," CEO Sridhar Ramaswamy said in a statement accompanying the earnings. With company offerings such as Snowflake Intelligence and Cortex Code, Ramaswamy said Snowflake was extending its role "from the trusted foundation for enterprise data and context to become the control plan for the agentic enterprise." Snowflake, which reported product revenue of $1.33 billion for the quarter, said it now has 779 customers spending more than $1 million on a trailing 12-month basis. The company raised its product revenue guidance for the entire fiscal year to $5.84 billion, up from previous guidance of $5.66 billion. Snowflake's stock price surged in after-hours trading in the wake of the news. While Snowflake shares closed at $175.26 Wednesday, down 1.32 percent from Tuesday's close, the price skyrocketed by $67.54 (more than 38.5 percent) to $242.80 by 8:00 p.m. EDT. Snowflake said the new SCA with AWS includes "deeper product integrations across generative AI and agentic AI, expanded go-to-market through AWS Marketplace, and joint investments in customer success programs, workload migrations, and strategic industry solutions designed to help enterprises move from AI experimentation to production-scale outcomes." In the announcement Ramaswamy said that through the agreement, Snowflake and AWS are "making it easier for enterprises to bring AI directly to governed data." Under the partnership Snowflake will leverage high-performance Graviton processors running in AWS data centers for such tasks as AI model training and inference. Snowflake will also expand its global footprint in AWS data centers with launches completed or underway in 10 new regions including Auckland, New Zealand; Capetown, South Africa; Bangkok, Thailand; the AWS European Sovereign Cloud, and others. The SCA also includes new joint initiatives to boost Snowflake sales through the AWS Marketplace, which exceeded $2 billion in calendar 2025, through simplified contracting and faster procurement processes. Snowflake and AWS are expected to further demonstrate their enterprise AI efforts at the Snowflake Summit 26 event in San Francisco next week. Natoma Acquisition With the Natoma acquisition Snowflake said it will gain the ability to "establish a natively integrated governance and identity layer for AI agents and MCP tool access," a move that will make it easier for customers to securely connect and manage how AI systems interact with their enterprise applications, databases, APIs and tools, Snowflake said in the acquisition announcement. Natoma's capabilities will be integrated into Snowflake's AI Data Cloud, the company said, "and available to customers soon." "By extending governance to AI-driven workflows, Snowflake makes it easier for companies to safely manage not just their data, but also the actions AI agents take across business workflows," the company said. Terms of the acquisition were not disclosed and a timeline for its completion was not provided.

Snowflake Expands AWS Partnership with $6 Billion Commitment to Accelerate Enterprise Agentic AI Adoption

Snowflake announced that it has signed a multi-year strategic collaboration agreement (SCA) with Amazon Web Services (AWS) to accelerate enterprise agentic AI adoption to help joint customers worldwide build and deploy AI faster and more securely. Snowflake announced that it has signed a multi-year strategic collaboration agreement (SCA) with Amazon Web Services (AWS) to accelerate enterprise agentic AI adoption to help joint customers worldwide build and deploy AI faster and more securely. As part of the expanded collaboration, Snowflake is making a $6 billion multi-year infrastructure commitment to AWS, its largest to date, reflecting the accelerating enterprise demand for AI and data workloads running on AWS.

Snowflake Commits $6 Billion to AWS For Global AI Expansion | PYMNTS.com

With this agreement, the companies aim to accelerate enterprise agentic AI adoption by helping their joint customers around the world build and deploy AI, Snowflake said in a Wednesday (May 27) press release. The agreement expands an existing collaboration between Snowflake and AWS. Snowflake was founded on AWS 11 years ago, most of its customers run on AWS today, and AWS recognizes Snowflake as a leading partner in driving customer adoption, according to the release. With the expanded agreement, the companies will develop deeper product integrations across generative AI and agentic AI, expanded go-to-market through AWS Marketplace, and joint investments in customer success programs, workload migrations and strategic industry solutions to help enterprises implement AI, per the release. "With AWS, we are making it easier for enterprises to bring AI directly to governed data, so they can move faster, operate with greater clarity, and create measurable impact at scale," Snowflake CEO Sridhar Ramaswamy said in the release. AWS CEO Matt Garman said in the release that enterprises are putting agentic AI to work after initially experimenting with AI. "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," Garman said. Snowflake announced in another Wednesday press release that it signed a definitive agreement to acquire Natoma, an enterprise Model Context Protocol (MCP) platform for AI agents, to make it easier to securely connect and manage how AI systems interact with enterprise applications, databases, APIs and tools. The company said the closing of the acquisition is subject to customary closing conditions. The company also announced its first quarter financial results Wednesday, saying that its revenue grew 33% year over year to reach $1.39 billion and that "AI continues to be a powerful tailwind for Snowflake."

Snowflake and AWS Strike $6B Deal to Power Enterprise Agentic AI

The collaboration brings generative and agentic AI capabilities directly to enterprise data to help joint customers build and deploy AI-powered applications faster and more securely Snowflake today announced that it has signed a multi-year strategic collaboration agreement (SCA) with Amazon Web Services (AWS) to accelerate enterprise agentic AI adoption to help joint customers worldwide build and deploy AI faster and more securely. As part of the expanded collaboration, Snowflake is making a $6 billion multi-year infrastructure commitment to AWS, its largest to date, reflecting the accelerating enterprise demand for AI and data workloads running on AWS. Snowflake was founded on AWS eleven years ago, and that foundation has grown into one of enterprise software's broadest and deepest collaborations. The majority of Snowflake's customers run on AWS today, with AWS recognizing Snowflake as a leading partner driving global customer adoption. The latest agreement builds on this momentum with deeper product integrations across generative AI and agentic AI, expanded go-to-market through AWS Marketplace, and joint investments in customer success programs, workload migrations, and strategic industry solutions designed to help enterprises move from AI experimentation to production-scale outcomes. "AI has generated enormous excitement, but for enterprises, the real challenge and opportunity is turning intelligence into action," said Sridhar Ramaswamy, CEO of Snowflake. "We are moving into the era of the agentic enterprise, where AI systems don't just answer questions, but help organizations reason over trusted data, coordinate workflows, and drive real business outcomes. With AWS, we are making it easier for enterprises to bring AI directly to governed data, so they can move faster, operate with greater clarity, and create measurable impact at scale." "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." Bringing AI to Where Enterprise Data Lives AI is only as powerful as the data behind it. The expanded collaboration is anchored in a technical architecture that brings foundation models directly to governed enterprise data, eliminating the complexity and risk of moving sensitive information between systems. Snowflake Cortex AI enables customers to build and deploy AI applications for text-to-SQL, summarization, sentiment analysis, and entity extraction directly within their Snowflake environment. Enterprises are rapidly adopting these capabilities to run AI on trusted, governed data without moving it outside their secure perimeter. Snowflake leverages AWS Graviton processors, delivering significant price-performance improvements for customers, and utilizing high performance, GPU-accelerated Amazon EC2 instances for AI model training and inference. Accelerating AI Adoption with AWS Since Snowflake first became available in AWS Marketplace, customers have embraced it as the fastest path to procure and deploy Snowflake's AI and data capabilities - surpassing $7 billion in lifetime sales and exceeding $2 billion in calendar year sales in 2025, more than doubling transaction growth year-over-year. The expanded SCA builds on that trajectory, scaling joint initiatives to help even more customers discover, procure, and deploy AI and data solutions through AWS Marketplace with simplified contracting, faster procurement. Snowflake has also continued expanding 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 European Sovereign Cloud, and others to help customers meet data residency requirements and deploy AI closer to where their business operates. 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 governed data to drive measurable business impact. "AI is deeply embedded in how Fetch builds and operates every day, and our work with Snowflake and AWS is strengthening that foundation," said Daniel Block, General Manager of Revenue and Partnerships, Fetch. "With Snowflake Cortex AI, we've deployed a semantic agent that allows our sales teams to query campaign data in natural language and get instant insights. This enables faster, more informed decision-making across our business to deliver more value for our brand partners." "Snowflake on AWS is the foundation that many of our customers rely on to move fast with data," said Caitlin Colgrove, Co-Founder and CTO, Hex. "For teams using Hex to explore, analyze, and build with AI, having that layer be secure, governed, and performant isn't a nice-to-have -- it's what makes enterprise AI adoption real." Snowflake and AWS will further demonstrate their shared vision for enterprise AI at Snowflake Summit 26.

Snowflake raises annual product revenue forecast as enterprises ramp up AI workloads

May 27 (Reuters) - Cloud-based data analytics platform Snowflake raised its annual product revenue forecast on Wednesday, signaling growing demand for AI-driven workloads and cloud migrations. The company's growth was fueled by surging enterprise demand for its core data warehousing products and growing uptake of its AI offerings, with migrations from legacy systems and increased use of machine learning tools adding momentum. Snowflake enables businesses to store, analyze and share large volumes of data across applications and users. The company has seen strong adoption of AI tools such as Cortex Code and Snowpark, which help businesses build generative AI applications and deploy machine learning models on their data. Snowflake raised its product revenue forecast for fiscal 2027 to $5.84 billion, from $5.66 billion projected earlier. "We now have 779 customers spending more than $1 million on a trailing 12-month basis," finance chief Brian Robins said. It expects second-quarter product revenue to be between $1.415 billion and $1.420 billion, compared with analysts' average estimate of $1.37 billion, according to data compiled by LSEG. Total revenue for the first quarter came in at $1.39 billion, above the estimate of $1.32 billion. (Reporting by Harshita Mary Varghese in Bengaluru; Editing by Shilpi Majumdar)