Snowflake Inc.

Good day, ladies and gentlemen. Thank you for joining today's Snowflake Q4 FY26 earnings call. My name is Tia, and I will be your moderator for today's call. All lines will be muted during the presentation portion of the call, with an opportunity for questions and answers at the end. If you would like to ask a question, please put a star 1 on your telephone keypad. I would now like to pass the call over to your host, Catherine McCracken, Head of Investor Relations. Please proceed.

Good afternoon, and thank you for joining us on Snowflake's fourth quarter fiscal 2026 earnings call. Joining me on the call today are Sridhar Ramaswamy, our chief executive officer, Brian Robbins, our chief financial officer, and Christian Kleinerman, our executive vice president of product, who will participate in the Q&A session. During today's call, we will review our financial results for the fourth quarter fiscal 2026, and discuss our guidance for the first quarter and full year fiscal 2027. During today's call, we will make forward-looking statements, including statements related to our business operations and financial performance. These statements are subject to risks and uncertainties, which could cause them to differ materially from our actual results. Information concerning these risks and uncertainties is available in our earnings press release, our most recent Forms 10-K and 10-Q, and our other SEC reports. All our statements are made as of today based on information currently available to us. Except as required by law, we assume no obligation to update any such statements. During today's call, we will also discuss certain non-GAAP financial measures, see our investor presentation for the definitions of the non-GAAP financial measures, and a reconciliation of GAAP to non-GAAP measures and business metric definitions, including adoption. The earnings press release and investor presentation are available on our website at investors.snowflake.com. A replay of today's call will also be posted on the website. With that, I would now like to turn the call over to Sridhar.

Thank you, Catherine. And thank you all for joining us today. This past year has been transformative for every business. A year ago, we were talking about the promise of AI. Today that promise is real and Snowflake sits at the center of the enterprise AI revolution. Across the market, AI is reshaping the software landscape, redefining categories and competitive dynamics. In our view, this is creating a clear separation between systems that demonstrate intelligence and platforms that can deploy it safely and at scale. The winners will be the platforms that combine trusted enterprise data govern business metrics, secure execution, and broad model choice, and make all of it easy to use. That's exactly what Snowflake was built to do. We deliver the data foundation enterprises rely on across clouds and across data types with the performance, reliability, and operational simplicity required for mission-critical workloads. As AI agents become central to how work gets done, those same capabilities become even more valuable because agents are only as powerful as the data they can access and the governance and security that surround it. You can see that leadership in what we shipped this year. With Snowflake Intelligence, we brought enterprise-grade agent capabilities directly to business teams. With the general availability of Cortex code, we extended that to builders, accelerating the entire data lifecycle and helping customers move faster from development to production. Most recently, we expanded Cortex-Code CLI to encompass data systems as we work towards simplifying how all of them are used in practice. The general purpose agent capabilities of Cortex-Code CLI combined with our AI-ready data on Snowflake are already driving meaningful operational impact just weeks after launch. Snowflake Intelligence and Cortex-Code are meaningful steps in Snowflake's evolution. On the platform where enterprises govern and analyze their data, to the platform where they build and run AI-native applications and workflows. Turning to our results, product revenue in Q4 grew 30% year over year to reach $1.23 billion. Remaining performance obligations totaled $9.77 billion, with year over year growth accelerating to 42%. Our net revenue retention was at a healthy 125%. Thanks to AI, we are both scaling revenue and becoming operationally more efficient. Fiscal 26 non-GAAP operating margin reached 10.5%, expanding more than 400 basis points year over year, reflecting our continued focus on operational rigor. Stock-based compensation declined meaningfully from 41% of revenue in fiscal 25 to 34% in fiscal 26, and we expected to further decrease to 27% of revenue in fiscal 27. This year's results are a testament that the AI Data Cloud continues to deliver tremendous value to our more than 13,300 customers across every stage of the data lifecycle. Built with deep product cohesion, Snowflake is easy to use, seamlessly connected for collaboration, grounded in the security and governance enterprises trust. As we innovate, we remain maniacally focused on driving great business outcomes for our customers. That focus is why leading organizations continue to choose Snowflake as the foundation for their data and AI strategies. We added 2,332 net new customers this year, and we are seeing more and more businesses move over to Snowflake. Seagate, for example, is modernizing its data foundation to better support its mission of powering data-driven innovation at global scale. By consolidating a massive data environment on Snowflake, the company is moving away from legacy infrastructure onto a platform built for scalability, reliability, and predictable cost, enabling teams across the business to access high-performance AI-ready analytics and make faster, more informed decisions. Our core business remains strong and AI is expanding workloads across our platforms. Capital One is a great example of how we are deepening our relationships with key customers. As Capital One scales its AI initiatives, they are leveraging Snowflake to unify proprietary data, optimize engineering workloads, and deliver AI-driven analytics across the enterprise. Key to our growth is the strength and momentum around our AI products. This quarter, We delivered the largest sequential increase in accounts using AI, bringing the total to more than 9,100 accounts. And in just three months, Snowflake Intelligence has scaled from a nascent offering to an essential capability for over 2,500 accounts, almost doubling quarter over quarter. For example, Peridot Motor Europe, a global automotive leader, is leveraging Snowflake Intelligence to revolutionize its operations. By enhancing enterprise search with EZDO's Knowledge Chatbot, and streamlining contract management through Document AI. Toyota has fundamentally shifted its development timelines, reducing AI agent deployment from months to weeks, creating a significant competitive advantage. And United Rentals, a global leader in equipment rentals, is using Snowflake Intelligence to power a new business intelligence agent that helps teams across more than 1,600 branches get real-time answers from their financial and operational data using natural language. The agent enables faster, more consistent decision-making for frontline managers. United Rentals is also using Snowflake's Cortex code to accelerate the development and testing of additional AI agents, scaling trusted intelligence across the business. And that's just the start of what Cortex code can do. It's a truly transformational coding agent that's already helping over 4,400 customers build, and scale AI-powered applications, and massively accelerating their ability to deploy production-grade AI. The chief technology officer of one of our partners, Evolve Consulting, described Cortex Core's impact on their business, saying, quote, 20 days, 21,000 operations, over 600 hours of work delivered. That is 16 work weeks compressed into less than a month. Development cycles that used to require extensive research, trial and error, and debugging now flow naturally through AI-assisted iteration. We're using this capability to accelerate how we bring new workloads onto Snowflake for our customers. End quote. Cortex Code meaningfully expands the surface of AI development on our platform and reinforces Snowflake as the enterprise AI foundation. As we look forward, we continue to see immense opportunity to support enterprises across the data lifecycle, and we are innovating rapidly opportunity. This year, we launched over 430 product capabilities, underscoring the strength of our product velocity. We are broadening how data enters and flows through Snowflake. Snowflake OpenFlow, now generally available, makes it easier than ever to bring in structured, unstructured, batch, or streaming data into the platform. We've also deepened how applications are built on Snowflake. Now generally available, Snowflake Postgres is a world-class operational database built directly onto the Snowflake platform, enabling developers to build and run production-grade transactional applications with the performance, reliability, and ecosystem of Postgres fully managed and governed within Snowflake. This transforms Snowflake from a system you analyze with into a platform that you build on. And our recent acquisition of Observe, a market-leading observability platform, extends the value that Snowflake can deliver. By integrating observability directly with data and AI products, we reduce complexity and enable faster, more reliable operations at scale. This expands our opportunity into the $50 billion IT operations market and positions Snowflake to lead a next-generation AI-powered observability. At the same time, we are strengthening the ecosystem around the platform Our landmark partnership with SAP is delivering incredible value, helping customers like Expand Energy unite mission-critical business data across their core systems within our AI data club. Our deepened partnership with Anthropic is already helping customers like Intercom see significant impact. Snowflake provides the secure, governed data foundation that Intercom's AI is built on. By applying direct AI capabilities to this data, including their use of Anthropics Cloud models, Intercom automates customer support at scale. This allows it to handle significantly higher support volumes with greater consistency and lower operational burden, especially for large, complex customers. We also recently announced a $200 million expanded partnership with OpenAI. It brings OpenAI's models natively into Snowflake to help our customers innovate faster while keeping their data secure and governed. And through our partnership with Google Cloud, customers now have access to the latest Gemini models natively within Snowflake, further expanding model choice and availability. As we innovate, we are scaling efficiency. Work is fundamentally changing, and we are leading this transformation both within Snowflake and across the industry. In many cases, we are creating entirely new AI-native systems built directly on Snowflake. Across our business, Snowflake Intelligence and Cortex Code are already delivering measurable results. Our service delivery team can complete customer projects up to five times faster, improving response accuracy by more than 25%, and compress implementation cycles from days to hours to drive 40% to 50% higher project margins and enabling customers to go live more than 40% faster. We have seen our site reliability engineering investigations that once required hours across multiple engineers now result in minutes, dramatically reducing resolution times and further strengthening Snowflake's reliability. And we have built agentic capabilities that help our sellers prioritize accounts, automate research, and generate personalized outreach projected to recoup the equivalent of 90 full-time engineers of productivity this year. Our finance team is working on automating travel and expenses analysis, proactively curbing auto policy behavior, an initiative that is expected to drive millions in annual savings. And we're seeing this transformation within our customers as well. They are leveraging agents not just to analyze information, but to automate complex workflows, and in some cases, retiring entire categories of previously used software systems. Take Sanofi, for example. AI-powered workflows built on Snowflake with partners like Elementum are replacing their traditional software systems used for processes like software license and invoice management. By running these workflows directly in Snowflake, Sanofi is streamlining operations while keeping its data securely within the platform. This is where the enterprise is heading. And we believe Snowflake is uniquely positioned to become the control plane for the agentic era. We've built the conditions that make agents safe, scalable, and enterprise-ready, covering a single enterprise-wide source of truth, governed metrics and shared business definitions, cross-cloud and cross-domain interoperability, built-in security, auditability, and governance. Our continued rapid innovations Tight go-to-market alignment and operational discipline are all in high gear to capture this opportunity, and we see a long runway of durable high growth and continued margin expansion ahead. Now, I'll turn it over to Brian to take us through the financial details.