Snowflake Inc.SNOW

Snowflake acquired Natoma Labs, an enterprise Model Context Protocol platform for AI agents.

“On June 3, 2026, the Company acquired all of the outstanding capital stock of Natoma Labs, Inc. (Natoma), an enterprise Model Context Protocol platform for AI agents. The Company acquired Natoma primarily for its developed technology and talent. The Company has accounted for this transaction as a business combination.”

Snowflake acquired Natoma Labs, an enterprise Model Context Protocol platform for AI agents.

“On June 3, 2026, we acquired all of the outstanding capital stock of Natoma Labs, Inc. (Natoma), an enterprise Model Context Protocol platform for AI agents. The preliminary purchase consideration was $128.3 million, which was comprised primarily of approximately 0.5 million shares of our common stock valued at $110.5 million as of the acquisition date and $17.7 million in cash. In connection with this business combination, we also issued to certain of Natoma’s employees a total of approximately 0.2 million shares of our common stock. These shares are subject to vesting agreements pursuant to which the shares will vest over three years, subject to each of these employees’ continued employment with us or our affiliates. The $54.4 million fair value of these shares is accounted for as post-combination stock-based compensation over the requisite service period of three years.”

Snowflake notes rapid growth and new AI product features including agentic AI models.

“Our revenue was $1.5 billion and $1.1 billion for the three months ended July 31, 2026 and 2025, respectively. As a result of our historical rapid growth, limited operating history, large number of new product features, including those incorporating artificial intelligence (AI) (including machine learning, large language, and other generative or agentic AI models, and software functionality to operationalize the foregoing), and unstable macro- and microeconomic conditions, our ability to accurately forecast our future results of operations, including revenue, gross margin, remaining performance obligations (RPO), and the percentage of RPO we expect to recognize as revenue in future periods, is limited and subject to a number of uncertainties, including our ability to plan for and model future growth and platform consumption. Our historical revenue growth should not be considered indicative of our future performance.”

Snowflake competes on ability to offer state-of-the-art AI models and agentic AI solutions.

“We compete based on various factors, including price, performance, product features, breadth of use cases, multi-cloud availability, ability to offer state-of-the-art AI models and agentic AI solutions, brand recognition and reputation, customer support, technical services, and differentiated capabilities, including ease of implementation and data migration, ease of administration and use, scalability and reliability, data governance, security and compatibility with existing standards, programming languages, third-party products, and the ability to operate in hybrid environments. Many of our competitors have substantially greater brand recognition, customer relationships, and financial, technical, and other resources than we do, and may be able to respond more effectively than us to new or changing opportunities, technologies, standards, customer requirements, and buying practices. Some of our privately-held competitors also have greater operational flexibility than we do, including the ability to make strategic long-term business decisions without the short-term financial performance pressure, market expectations, and public disclosure obligations that affect public companies. In addition, we may not be able to respond to market opportunities as quickly as smaller companies or offer as many discounts or free services as our competitors. Our support of open data formats may also reduce switching costs between us and our competitors.”

Snowflake acquired TensorStax which built autonomous AI agents and Natoma for AI agents.

“We have in the past and may in the future seek to acquire or invest in businesses, joint ventures, and platform technologies that we believe could complement or expand our platform, enhance our technology, or otherwise offer growth opportunities. For example, since the beginning of fiscal 2026, we have acquired several companies, including Crunchy Data Solutions, Inc., a privately-held company that provided PostgreSQL technology; TensorStax, Inc., a privately-held company that built autonomous AI agents for data engineering services; Observe, Inc., a privately-held company that built an AI-powered observability platform; and Natoma Labs, Inc. (Natoma), an enterprise Model Context Protocol platform for AI agents. Such transactions have in the past and may in the future divert the attention of management and cause us to incur various expenses in identifying, investigating, financing, and pursuing suitable opportunities, whether or not the transactions are completed, and may result in unforeseen operating difficulties and expenditures. In particular, we have encountered and may continue to encounter difficulties or unexpected costs integrating the businesses, technologies, products, personnel, contracts or operations of any acquired companies, particularly if the key personnel of an acquired company choose not to work for us, their software is not easily adapted to work with our platform, or we have difficulty retaining the customers, suppliers, or partners of any acquired busin”

Snowflake agreed to acquire Natoma Labs, an enterprise Model Context Protocol platform for AI agents.

“On May 24, 2026, the Company entered into a definitive agreement to acquire all outstanding capital stock of Natoma Labs, Inc., an enterprise Model Context Protocol platform for AI agents, for total stated consideration of approximately $ 110.0 million, consisting primarily of the Company’s common stock (Equity Consideration) with the remainder in cash. Based on the Company’s preliminary estimates, approximately 30 % of the Equity Consideration will be subject to certain vesting conditions, the acquisition-date fair value of which will be accounted for as post-combination stock-based compensation over a requisite service period. The transaction is expected to close in June 2026, subject to satisfaction of certain closing conditions.”

Snowflake agreed to acquire Natoma Labs, an enterprise Model Context Protocol platform for AI agents.

“On May 24, 2026, we entered into a definitive agreement to acquire all outstanding capital stock of Natoma Labs, Inc., an enterprise Model Context Protocol platform for AI agents, for total stated consideration of approximately $110.0 million, consisting primarily of the Company’s common stock with the remainder in cash. The transaction is expected to close in June 2026, subject to satisfaction of certain closing conditions.”

Snowflake acquired TensorStax, which built autonomous AI agents for data engineering.

“We have in the past and may in the future seek to acquire or invest in businesses, joint ventures, and platform technologies that we believe could complement or expand our platform, enhance our technology, or otherwise offer growth opportunities. For example, since the beginning of fiscal 2026, we have acquired several companies, including Crunchy Data Solutions, Inc., a privately-held company that provided PostgreSQL technology; TensorStax, Inc., a privately-held company that built autonomous AI agents for data engineering services; and Observe, Inc. (Observe), a privately-held company that built an AI-powered observability platform. Such transactions have in the past and may in the future divert the attention of management and cause us to incur various expenses in identifying, investigating, financing, and pursuing suitable opportunities, whether or not the transactions are completed, and may result in unforeseen operating difficulties and expenditures. In particular, we may encounter difficulties or unexpected costs integrating the businesses, technologies, products, personnel, contracts or operations of any acquired companies, particularly if the key personnel of an acquired company choose not to work for us, their software is not easily adapted to work with our platform, or we have difficulty retaining the customers, suppliers, or partners of any acquired business due to changes in ownership, management, or otherwise. Any such transactions that we are able to complete ma”

Snowflake launched Cortex Code and Snowflake Intelligence for the Agentic Enterprise.

“"Snowflake delivered a milestone quarter, with product revenue of $1.33 billion, up 34% year-over-year, marking the strongest sequential dollar growth in our history,” said Sridhar Ramaswamy, CEO of Snowflake. “AI continues to be a powerful tailwind for Snowflake, and Q1 marks a clear inflection point in that journey. 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."”

Snowflake signed agreement to acquire Natoma, an enterprise platform for AI agents.

“• AI Acquisition : Signed a definitive agreement in May 2026 to acquire Natoma, an enterprise Model Context Protocol platform for AI agents, to make it easier for users to securely connect AI to the tools they use every day, directly within and beyond Snowflake. 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.”

Launched Snowflake Intelligence to enable customers to create data agents.

“Our platform supports a wide range of product categories that enable our customers’ most important business objectives, including analytics, data engineering, AI, and applications and collaboration. We are committed to expanding our platform’s product features and use cases and supporting developers in building their applications and businesses. Many of our product features help power multiple product categories. In 2021, we launched Snowpark for Java and Scala to allow developers to build in the language of their choice, and in 2022 we added support for Python. Snowpark brings the power of Python and Java to our platform and complements many use cases for our customers across several product categories, including data engineering and AI. In 2023, we launched Snowpark Container Services, a fully managed container platform designed to facilitate the deployment, management, and scaling of containerized applications and AI models within our ecosystem. Snowpark Container Services are used in several of our product categories, including AI and applications. In 2024 and 2025, we announced and then launched Snowflake Intelligence within our AI product category, to enable our customers to create data agents, empowering business users to take actions on structured and unstructured data without the need for technical knowledge or coding skills. In 2025 and 2026, we announced and then launched Snowflake Postgres within our new transactions product category, a fully managed Postgres offe”

Unified data and AI platform enables organizations to build and deploy AI agents.

“• AI. Our unified data and AI platform enables organizations to build and deploy AI agents and other AI functionality to:”

AI-powered Site Reliability Engineer agent leverages context graph for faster troubleshooting and issue resolution.

“• Leverage agentic AI for faster troubleshooting. With the AI-powered Site Reliability Engineer, leverage a unified context graph that correlates logs, metrics, and traces, allowing teams to detect anomalies earlier, identify root causes faster, and resolve production issues faster, to improve operational resilience as systems grow more distributed, dynamic, and autonomous.”

Snowflake promotes open architecture as foundation for operating next generation AI agents at scale.

“• Utilize an open-standard architecture built for scale. Manage massive telemetry volumes using economical object storage, elastic compute, and interoperable standards, an essential foundation for operating next generation AI agents and applications at scale.”

Snowflake partners can build and deploy AI agents using its data and AI platform and tools.

“Our partnership strategy is focused on delivering complete end-to-end solutions, driving general awareness, and broadening our global reach, and acts as a force multiplier for our direct sales and marketing efforts. Our Snowflake Partner Network is a global program comprising system integrators, technology, software, and data providers that integrate directly with the Snowflake AI Data Cloud to enhance functionality, improve performance, and accelerate data-driven insights. These partners play a critical role in sourcing leads, executing transactions, and delivering customer outcomes, while focusing on high-value enterprise AI initiatives and digital transformation services. We are deepening technical integrations with market-leading enterprise SaaS platforms to provide a zero-copy, bi-directional data fabric that enables “data-in-place” analytics and harmonizes mission-critical business data. Our unified data and AI platform enables our partners to build and deploy AI agents in the enterprise. By leveraging Snowflake Intelligence and Snowflake Openflow, our ecosystem partners can develop intelligent agents that act on cross-organizational knowledge, supported by automated data pipelines that simplify the deployment of production-ready AI applications. Our system integrator partners, including GSIs, help accelerate platform adoption and migration by providing specialized domain expertise and services for large-scale digital transformations. Furthermore, we provide an open pla”

Snowflake lists timely availability of enterprise-grade LLMs and AI agents as a risk factor.

“• use of AI and timely availability of leading, enterprise-grade large language models and AI agents;”

Snowflake launched Snowflake Intelligence enterprise AI agent with fastest adoption in company history.

““Snowflake delivered another strong quarter, with product revenue of $1.16 billion, up 29% year-over-year, and remaining performance obligations totaling $7.88 billion, up 37% year-over-year,” said Sridhar Ramaswamy, CEO of Snowflake. “Snowflake is the cornerstone for our customers’ data and AI strategies, driving real business impact at scale. Snowflake Intelligence, our enterprise AI agent, saw the fastest adoption ramp in Snowflake history and is transforming how businesses interact with their data, delivering real-time, actionable intelligence. Combined with our strategic partnerships with the world’s leading AI model providers, clouds and application platforms, Snowflake is supercharging the entire data lifecycle with AI-driven capabilities.””