What changed in this filing

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Item 1. Business

2026-03-20 compared with 2025-03-21 · 98 added, 62 removed, 331 unchanged (33% of the section changed)

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By offering rich primitives for data and applications, we believe that we can create a data connected world where organizations have seamless access to explore, share, and unlock the value of data.

Our vision is a world where data and AI turn possibilities into reality.

To realize this vision, we deliver the AI Data Cloud, a network where Snowflake customers, partners, developers, data providers, and data consumers can break down data silos and derive value from a growing number of data sets in secure, governed, and compliant ways.

Our platform is the innovative technology that powers the AI Data Cloud, enabling customers to consolidate data into a single source of truth to drive meaningful insights, apply AI to solve business problems, build data applications, and share data and data products.

We provide our platform through a customer-centric, consumption-based business model, only charging customers for the resources they use.

We provide our platform through a customer-centric, consumption-based business model.

Snowflake solves the decades-old problem of data silos and data governance.

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As a result, customers can blend existing data with new data for broader context, augment data science efforts, and create new monetization streams.

Delivered as a service, our platform requires near-zero maintenance, enabling customers to focus on deriving value from their data rather than managing infrastructure.

Our cloud-native architecture includes three independently scalable but logically integrated layers across compute, storage, and cloud services.

Delivered as a service, our platform requires near-zero infrastructure maintenance, enabling customers to focus on deriving value from their data rather than managing infrastructure.

Our cloud-native architecture includes three independently scalable but logically integrated layers across storage, compute, and cloud services.

The storage layer ingests massive amounts and varieties of structured, semi-structured, and unstructured data.

The compute layer provides dedicated resources to enable users to simultaneously access common data sets for many use cases with minimal latency.

The storage layer ingests massive amounts and varieties of structured, semi-structured, and unstructured data to create a unified data record.

The cloud services layer intelligently optimizes each use case’s performance requirements with no administration.

Within the compute layer, users can clean and prepare their data, including any required metadata and business semantics, to create governed, unified data records that are AI ready and are written back to the storage layer.

The cloud services layer enables users to securely use AI within applications, tools, and processes.

This architecture is built on three major public clouds across 53 regional deployments around the world.

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Snowpark Container Services are used in several of our product categories, including AI and applications.

In 2024, we announced 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 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 offering that enables customers to consolidate application and analytical data onto a single platform and build context-aware AI agents, deliver rich personalization and run powerful low latency analytics.

We continue to invest in our Native Application program to help companies build, operate, and market applications in the AI Data Cloud by supporting developers across all stages of the application journey.

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The number of customers that contributed more than $1 million in trailing 12-month product revenue increased from 576 to 733 as of January 31, 2025 and 2026, respectively.

For the fiscal years ended January 31, 2025, 2024, and 2023, our revenue was $3.6 billion, $2.8 billion, and $2.1 billion, respectively, representing year-over-year growth of 29% and 36%, respectively.

Our net loss was $1.3 billion, $838.0 million, and $797.5 million for the fiscal years ended January 31, 2025, 2024, and 2023, respectively.

See the section titled “Management’s Discussion and Analysis of Financial Condition and Results of Operations” for how we determine our customer count.

For the fiscal years ended January 31, 2026, 2025, and 2024, our revenue was $4.7 billion, $3.6 billion, and $2.8 billion, respectively, representing year-over-year growth of 29% in each period.

Our net loss was $1.3 billion, $1.3 billion, and $838.0 million for the fiscal years ended January 31, 2026, 2025, and 2024, respectively.

The Rise of the AI Data Cloud

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• Easy to use.

Our platform can be up and running in seconds and is priced based on a consumption-based business model, reducing hidden costs and ensuring customers pay only for what they use.

Our platform can be up and running in seconds and is priced based on a consumption-based business model, reducing hidden costs and helping ensure that customers pay only for what they use.

Snowpark, our developer framework, allows developers to interact with Snowflake through various popular programming languages, including Python.

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• Enable greater data access through enhanced data governance.

Security and governance, including the encryption of data in transit and at rest, are part of our core design values.

Security and governance, including the encryption of customer data at rest and in transit to and from our platform, are part of our core design values.

This provides customers with the confidence to share their data inside their organizations, as well as with their partners, customers, and suppliers, to unlock new insights and build new applications.

Our Growth Strategies

We intend to invest in our business to advance the AI Data Cloud through the adoption of our platform.

We intend to invest in our business to advance the AI Data Cloud through customers’ adoption of our platform.

Our growth strategies include:

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We intend to continue making significant investments in research and development and hiring top technical talent to enable new use cases, strengthen our technical lead in our platform’s architecture, and increase our differentiation through enhanced collaboration capabilities.

During the fiscal year ended January 31, 2025, capabilities like Iceberg tables, hybrid tables, notebooks, Internal Marketplace, Universal Search, Document AI, Snowflake Cortex AI, and Snowflake ML became generally available, while capabilities like lineage visualization interface, Snowflake Open Catalog, ML Operations, AI model sharing and model explainability became available in public preview, and are expected to become generally available in the fiscal year ending January 31, 2026.

During the fiscal year ended January 31, 2026, capabilities like Snowflake Intelligence, Snowflake Cortex Agents, Generation 2 Standard Warehouses, Interactive Tables and Interactive Warehouses, Workspaces, Managed MCP Server and Snowflake Openflow, and Snowpark Connect for Apache Spark TM became generally available, while capabilities like Snowflake Postgres, Snowflake Cortex Code, and Semantic View Autopilot became generally available during the first quarter of our fiscal year ending January 31, 2027.

• Drive growth by acquiring new customers.

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• Grow and invest in our partner network.

Our Snowflake Partner Network is comprised of system integrators, resellers, data providers, and other services partners who help accelerate the adoption of our platform, and technology partners, who help provide end-to-end solutions to our customers.

We plan to continue investing in building out our partner program to drive more consumption on our platform, broaden our distribution footprint, acquire new customers, and drive greater awareness of our platform.

Partners can participate in programs like AI Competencies, Industry Competencies, Snowpark Accelerated, and Governance Accelerated to receive special support from Snowflake technical experts.

Our Snowflake Partner Network is comprised of system integrators, technology, software, and data providers that help broaden our distribution footprint, acquire new customers, and drive greater awareness of our platform.

We are scaling the AI Data Cloud through high-impact alliances with enterprise SaaS platforms to harmonize mission-critical data, and Global System Integrators (GSIs) to drive large-scale digital transformations.

Additionally, strategic partnerships with foundational model providers deliver state-of-the-art models natively within Snowflake Cortex AI.

Through these high-value alliances, we seek to maintain model neutrality, enabling enterprises to securely deploy frontier models while establishing Snowflake as the trusted, independent foundation for enterprise AI.

These efforts, supported by initiatives like Snowflake Intelligence and specialized AI and Industry Competencies, help ensure our ecosystem provides the comprehensive end-to-end solutions required to accelerate platform adoption and consumption.

Our platform unifies data and supports a growing variety of product categories, including analytics, data engineering, AI, and applications and collaboration.

Customers can leverage our platform for any one of these products, but when taken together, they provide an integrated, end-to-end solution that delivers greater insights, faster data transformations, improved data sharing, and accelerated application development.

Delivered as a service, our platform is deployed across multiple public clouds and regions, is easy to use, and requires near-zero maintenance.

Delivered as a service, our platform is deployed across multiple public clouds and regions, is easy to use, and requires near-zero infrastructure maintenance.

Product Categories

Organizations use our platform to power the following product categories:

Our platform provides reporting and analytics to improve business intelligence.

For Analytics, our platform enables organizations to:

◦ Support multiple users and activities concurrently.

Enable multiple activities, such as repeatable analytics, rendering of dashboards, or ad hoc explorations, such as data science model training, with flexible compute capacity, no resource contention, and no provisioning of any infrastructure.

◦ Generate comprehensive data insights.

Run queries on structured, semi-structured, and unstructured data to capitalize on a more comprehensive view of their data to drive maximum insights.

◦ Simplify data governance.

Gain immediate insight into data and usage patterns and set policies and configurations to maximize governance.

◦ Simplify development by uniting transactions and analytical data.

Analytics includes Unistore, which, using hybrid tables, allows our customers to develop lightweight transactional use cases like serving data or storing an application’s state, all within our platform.

Unistore also enables customers to quickly analyze transactional and historical data from across the organization’s ecosystem, build new and better customer experiences, and get deeper insights by integrating transactional and analytical data in a single data set.

• Data Engineering.

Our platform enables organizations to efficiently build and manage streaming and batch data pipelines in SQL or Python for downstream consumers like data science teams, analytics teams, and business applications.

For Data Engineering, our platform enables organizations to:

Data Engineering is the process of collecting, cleaning, and organizing large amounts of data using production-grade data pipelines so that the data is optimized for further use.

Our Data Engineering products enable organizations to efficiently build and manage streaming and batch data pipelines in SQL or Python for downstream consumers like data science teams, analytics teams, and business applications.

For example, our Data Engineering products enable organizations to:

◦ Drive faster decision making.

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◦ Enact better governance and security to enable broader data access.

Simplify data governance and provide rich security and controls to help ensure data is managed and accessed according to regulatory and corporate requirements.

Our unified data and AI platform enables organizations to build and deploy large language models (LLMs), ML models, and other AI functionality to:

Simplify data governance and provide rich security tools and controls to help organizations ensure that their data is managed and accessed according to regulatory and corporate requirements.

Analytics is the process of examining data to uncover patterns, trends, and insights that enable better decision making.

Accordingly, our Analytics product category provides reporting and analytics to improve business intelligence and enables organizations to:

◦ Support multiple users and activities concurrently.

◦ Generate comprehensive data insights.

Run queries on structured, semi-structured, and unstructured data to capitalize on a more comprehensive view of their data to drive maximum insights.

◦ Simplify data governance.

Gain immediate insight into data and usage patterns and set policies and configurations to maximize governance.

• Transactions.

The Transactions category includes products related to operational databases optimized for many small, concurrent reads and writes that must be recorded correctly at low latency.

Our Transactions products unify transactional and analytical processing on a single, enterprise-ready platform, without complex data pipelines.

Accordingly, our Transactions product category enables organizations to:

◦ Simplify development by uniting transactions and analytical data.

Using hybrid tables, Unistore allows our customers to develop lightweight transactional use cases like serving data or storing an application’s state, all within our platform.

◦ Unify Postgres and analytics to eliminate complex data pipelines.

Bringing the reliable and trusted transactional database capabilities of Postgres to the Snowflake platform, Snowflake Postgres enables customers to run transactional workloads alongside their analytical workloads within a unified platform.

Data can be replicated quickly and easily between Postgres and Snowflake, creating a single source of truth across databases and eliminating costly data pipeline.

Our unified data and AI platform enables organizations to build and deploy AI agents and other AI functionality to:

◦ Transform unstructured data into insights.

Efficiently and securely run natural language processing tasks (such as summarization, translation, and categorization) on unstructured data at scale using Document AI and Cortex LLM Functions.

Efficiently and securely run natural language processing tasks (such as summarization, translation, and categorization) on unstructured data at scale using AI_EXTRACT and Cortex LLM Functions.

◦ Develop conversational assistants on enterprise data.

Interact with data via conversational applications that can answer ad hoc user queries by combining language models in Cortex AI with real-time structured data retrieval using Cortex Analyst and unstructured data retrieval using Cortex Search.

◦ Build and deploy LLMs, ML and embedding models.

◦ Build and deploy ML and embedding models.

Train and deploy ML models, fine-tune embedding and language models customized with proprietary data to deliver results tailored to a specific industry or organization using the Snowflake ML development suite of services and Snowpark Container Services, a graphics processing unit (GPU)-powered, managed compute service.

• Applications.

Our Applications product category enables the development, enablement, and use of applications built on the Snowflake platform.

Our platform can power new applications as well as enable existing applications with capabilities for AI, reporting, and analytics.

For Applications, our platform enables organizations to:

For example, our platform enables organizations to:

◦ Develop analytical AI applications.

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• Collaboration .

Our platform enables organizations to securely share, monetize, and acquire live data, applications, and AI products.

For Collaboration, our platform enables organizations to:

Our Collaboration product category enables organizations to securely share, monetize, and acquire live data, applications, and AI products.

For example, our platform enables organizations to:

◦ Securely share live data .

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Invite customers, suppliers, and partners to securely access their data, streamline operations, and increase transparency.

◦ Easy data replication.

◦ Easily replicate data.

Our platform allows for easy replication of data, accounts, policies, and pipelines for multiple users across multiple public cloud providers and regions without compromising data integrity and governance, enabling our customers and their users to rely on a single source of truth and achieve cross-cloud business continuity.

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We built our platform with security as a core shared responsibility between us and our customers.

Our platform provides a number of configurable capabilities for customers to confidently use our platform while preserving the security requirements of their organizations, including:

Our platform provides a number of configurable capabilities for customers to confidently use our platform while configuring security requirements for their organizations, including:

◦ Authentication.

Our platform supports a number of authentication capabilities, including federated authentication with a variety of identity providers, as well as support for multi-factor authentication.

Our platform supports a number of customer-configurable authentication capabilities, including federated authentication with a variety of identity providers, as well as support for multi-factor authentication.

◦ Access control.

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◦ Data encryption.

Our platform encrypts all customer data uploaded to our platform, both at rest and in transit over untrusted networks, and simplifies operations by providing automatic re-keying of data.

Our platform encrypts customer data uploaded to our platform, both at rest and in transit over untrusted networks to and from our platform, and simplifies operations by providing automatic re-keying of data.

It also supports customer-managed keys, where an additional layer of encryption is provided by keys controlled by customers, giving them the ability to control access to the data.

Observe by Snowflake

In February 2026, we acquired Observe, Inc.

(Observe), a leader in AI-powered observability, to deliver the next generation of AI-powered observability, built on open standards and designed for the scale, complexity, and economics required by modern AI-driven enterprises.

Observe enables organizations to manage enterprise-wide observability across terabytes to petabytes of telemetry with an open, scalable architecture and AI-powered troubleshooting workflows.

For example, Observe enables organizations to:

• 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.

• 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.

• Retain full telemetry data with efficient economics.

Retain high-fidelity telemetry data, optimizing observability cost while improving visibility enterprise-wide.

Sales and Marketing

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Our direct sales team is primarily focused on new customer acquisitions and driving increased use of our platform by existing customers.

The breadth of our platform allows us to engage at every level of an organization, including data analysts and data engineers through our self-service model and senior executives through our direct sales team.

The substantial majority of our global sales and marketing efforts are carried out by teams located in North America.

The breadth of our platform allows us to engage at every level of an organization, including data analysts, data engineers, and developers through our self-service model and senior executives through our direct sales team.

The majority of our global sales and marketing efforts are carried out by teams located in North America.

Outside of North America, we have dedicated direct sales teams for the EMEA and APJ regions for organizations of all sizes.

In addition to direct sales, we also sell our platform through resellers and distributors.

Many organizations initially adopt our platform through a self-service trial on our website.

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Our marketing team combines the creation of inbound demand with direct marketing, business development, and efforts targeted at business and technology leaders.

Our partnership strategy is focused on delivering complete end-to-end solutions for our customers, driving general awareness of our platform, and broadening our distribution and reach to new customers.

Our Snowflake Partner Network is a global program that manages our business relationships with a broad-based network of companies.

Our partnerships consist of channel partners, system integrators, data providers, applications, AI solutions, and other technology partners.

Collectively, these partners help us source leads, execute transactions, and deliver training, implementation, and business value for our customers.

Our system integrator partners help make the adoption of and migration to our platform easier by providing implementations, value-added professional services, managed services, and resale services.

Our technology partners provide strategic value to our customers by providing software tools, such as data loading, business intelligence, AI, data governance, and security, as well as data sets and applications on the Snowflake Marketplace, to augment the capabilities of our platform.

We continue to invest in formal alliances with the leading consulting, data management, and implementation service providers to help our customers migrate their legacy database solutions to the cloud.

Additionally, with Snowflake Ventures, Snowflake is investing in key partners that are innovating with the AI Data Cloud, and we have over 1,100 partners in our Powered by Snowflake Start Up program, many of whom are building next-generation data-intensive applications.

Over time, we expect our partner network to drive more customers and consumption to our platform.

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 platform for foundational model providers to deliver leading AI models natively within our security perimeter.

Additionally, with Snowflake Ventures, we continue to invest in key partners that are innovating with the AI Data Cloud, and many partners in our Powered by Snowflake Start Up program are building next-generation data-intensive applications.

Over time, we expect our partner network to drive significant new customer acquisitions and sustained consumption on our platform.

Research and Development

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It is also responsible for operating and scaling our platform, including the underlying public cloud infrastructure.

Our research and development employees are located primarily in or around Bellevue, Washington and San Mateo, California in the United States, and internationally in Berlin, Germany;

Our research and development employees are located primarily in or around Bellevue, Washington and Menlo Park, California in the United States, and internationally in Berlin, Germany;

Toronto, Canada;

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• other established vendors of legacy database solutions or big data offerings;

• existing observability solution providers, particularly those with strong technological, marketing, and sales positions;

• new or emerging entrants seeking to develop competing technologies.

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• ability to elastically scale up and scale down in high-intensity use cases;

• ability to provide interoperability and integrations across open formats, tools, applications, and platforms;

• ease of deployment, implementation, and use;

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

• choice of programming language;

• performance, scalability, and reliability;

• ability to provide business continuity and disaster recovery across multiple public cloud providers;

• security and governance;

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As of January 31, 2026, we had 9,060 employees operating across 36 countries.

None of our employees are represented by a labor union with respect to his or her employment.

In certain countries in which we operate, we are subject to, and comply with, local labor law requirements, which include works councils and industry-wide collective bargaining agreements.

None of our employees in the United States are represented by a labor union with respect to his or her employment.

In certain countries in which we operate, we are subject to, and comply with, local labor law requirements, which include works councils, labor unions, and industry-wide collective bargaining agreements.

We have not experienced any work stoppages, and we consider our relations with our employees to be good.

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We are mindful that everyone has different experiences, and we use our differences to strengthen who we are.

Total Rewards

We have invested substantial time and resources in building our team, and we measure employee performance against our company values.

We are dependent on our management, highly-skilled software engineers, and sales personnel, and it is crucial that we continue to attract and retain valuable employees.

To facilitate attraction and retention, we strive to provide opportunities for our employees to grow and develop in their careers, supported by strong compensation and benefits programs.

We use a combination of fixed and variable cash compensation for all employees, and we award equity compensation to certain employees that is designed to align our employees’ interests with those of our stockholders.

Eligible employees are also able to participate in our 2020 Employee Stock Purchase Plan, which allows employees to purchase our stock at a 15 percent discount up to U.S.

Total Rewards and Talent Management

Our ability to execute our strategy depends on attracting and retaining a highly skilled workforce, particularly in software engineering, sales, and management.

To maintain a competitive advantage, we focus on three pillars:

• Competitive Compensation :

We utilize a mix of fixed and variable cash compensation designed to reward performance against defined business results and core values.

• Equity Alignment :

We grant equity awards to align employee interests with long-term stockholder value.

Additionally, our 2020 Employee Stock Purchase Plan (ESPP) allows eligible participants to purchase shares at a 15% discount up to U.S.

Internal Revenue Code limits.

We offer employees benefits that vary by country and are designed to meet or exceed local legal requirements and to be competitive in the marketplace.

• Global Benefits & Development :

We provide comprehensive benefits tailored to local markets that meet or exceed statutory requirements.

Beyond financial rewards, we invest in our human capital through structured career development and growth opportunities.

Intellectual Property

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Compliance with these laws, rules, and regulations has not had a material effect on our capital expenditures, results of operations, and competitive position as compared to prior periods.

Nevertheless, compliance with existing or future governmental regulations, including, but not limited to, those related to global trade, business acquisitions, consumer and data protection, AI Technology, environmental or related requirements or disclosures, and taxes, could have a material impact on our business in future periods.

Nevertheless, compliance with existing or future governmental regulations, including, but not limited to, those related to global trade, business acquisitions, consumer and data protection, AI, government contracts, environmental or related requirements or disclosures, and taxes, could have a material impact on our business in future periods.

For more information on the potential impacts of government regulations affecting our business, see the section titled “Risk Factors.”

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Compared sentence by sentence after normalising whitespace, quotation marks, case and digits, so re-formatting and restated figures do not read as changed language. Wording changes appear as one removal and one addition. The current filing and the prior one are authoritative.

What changed 10-K

Item 1. Business