Amplitude, Inc.

Good afternoon, everyone, and welcome to Amplitude's fourth quarter and full year 2025 earnings call. I'm John Strepa, head of investor relations, and joining me today are Spencer Skates, CEO and co-founder of Amplitude, and Andrew Casey, chief financial officer. During today's call, management will make forward-looking statements, including statements regarding our financial outlook for the first quarter and full year 2026, the expected performance of our products, our expected quarterly and long-term growth, investments, and our overall future prospects. These forward-looking statements are based on current information, assumptions, and expectations, and are subject to risks and uncertainties, some of which are beyond our control, that could cause actual results to differ materially from those described in these statements. Further information on the risks that could cause actual results to differ is included in our filings with the Securities and Exchange Commission. You are cautioned not to place undue reliance on these forward-looking statements, and we assume no obligation to update these statements after today's call except as required by law. Certain financial measures used on today's call are expressed on a non-GAAP basis. We use these non-GAAP financial measures internally to facilitate analysis of our financial and business trends and for internal planning and forecasting purposes. These non-GAAP financial measures have limitations and should not be used in isolation from or as a substitute for financial information prepared in accordance with GAAP. Additional information regarding these non-GAAP financial measures and a reconciliation between these GAAP and non-GAAP financial measures are included in our earnings press release and the supplemental financial information, which can be found on our investor relations website at investors.amplitude.com. With that, I'll hand the call over to Spencer.

Good afternoon, everyone, and welcome to Amplitude's fourth quarter and full year 2025 earnings call. Today, I'm going to cover three things. First, our strong Q4 results and progress in the enterprise. Second, how AI is driving demand for analytics and our strategy to deliver. Third, a look at our new AI agents in action and a spotlight on customer stories. Q4 represents one of the strongest quarters in Amplitude history. Our fourth quarter revenue was $91.4 million, up 17% year-over-year and exceeding the high end of our revenue guidance. Our annual recurring revenue was $366 million, up 17% year-over-year and up $18 million from last quarter. This was our highest net new ARR quarter since 2021. Non-GAAP operating income was 4.2 million or 4.6% of revenue. Customers with more than 100K in ARR grew to 698, an increase of 18% year over year. Over 25 AI companies are now included in that 100K cohort as well. This quarter, was marked by balanced execution. No single deal was over $1 million, yet we had our highest ever number of multi-product and 100K ARR LANs. I want to talk more about AI in our strategy. Over the past year, AI coding assistance from Anthropic, OpenAI, Cursor, and others have compressed development cycles dramatically. the velocity at which companies are shipping new products has accelerated. When software is this easy to build, it creates a gap between how fast teams can ship features and how fast they can learn if they are working. This shifts the pressure to the right side of the product development loop that you see here, the use and learn side. Understanding how users behave, what works and what doesn't, and what actions to take next becomes the bottleneck. The constraint is no longer knowing how to build. It is knowing what to build instead. This is the hardest problem in software today. I say that because builders and their AI assistants need a system of context that combines multiple data streams. They need structured behavioral data. They need the correct retention and funnel logic. and they need the right analytical tools exposed in a way that enables AI to reason effectively. The AI then needs to be able to iterate with that system, test hypotheses, refine queries, identify root causes, and recommend actions accurately and repeatedly. This is not something that can be bytecoded over a weekend or replicated accurately with an LLM on a data warehouse. However, it is exactly what Amplitude is purpose-built to do. We have worked with thousands of companies over the past 13 years in Amaski world's largest database of user behavior. Our AI can explore patterns, explain changes, and guide teams on what to do next more accurately and reliably than any other system. Over the past six months, our agentic analytics platform has reached a 76% success rate on complex production-grade queries. That is seven times better than a straight text-to-SQL approach. With the new agents we launched yesterday, teams can now move from insight to action in minutes, not weeks using analytics, cohorts, experiments, and messaging in one continuous agentic workflow. Through our MCP integrations with Anthropic, Figma, OpenAI, GitHub, Lovable, and Slack, we are bringing behavioral intelligence to teams where they already work. Understanding user behavior now becomes as simple as asking a question in a chat window. This puts Amplitude in a unique position. The frontier labs are pushing the boundaries of AI models and they recognize the complexity of analytics, experimentation, and behavioral understanding, so they turn to Amplitude. As I mentioned earlier, more than 25 of the leading AI-native companies, including some of the names you see here, are customers with over 100K in ARR with amplitude. In addition, one of the world's largest frontier AI labs is a seven-figure customer as well. They came to us to replace a manual system built from fragmented internal tools and raw warehouse data. Using Amplitude Enterprise Analytics and session replay, they can now understand activation, engagement, retention, and monetization end-to-end. With Amplitude MCP, they can offer those insights directly within the AI environments their teams already use, dramatically improving the ability for them to automate development. And it's not just AI companies. Companies of all sizes need a system that gives them trusted data, insights, and action to successfully deploy AI in the real world. So they turn to Amplitude as well. This momentum combined to one of our strongest quarters across gross bookings and new ARR alongside meaningful improvement in churn. Our go-to-market motion has matured. There is a tighter focus on value-based use cases in the enterprise and on expanding with multi-product deployments. We continue to consolidate the fragmented market. Platform win rates are increasing against point solutions, and our newer products are gaining traction. Guides and Surveys, launched less than a year ago, is our fastest growing product to date. We are also seeing a large increase in AI native usage as agents connect directly to Amplitude. Over the past few months, the total number of queries triggered by AI agents has increased dramatically. In October last year, there were almost none, and today it is 25%. Agents also drove the vast majority of overall incremental query growth. This tells us that customers are trusting agents with analytics work. It also indicates that our platform offers the accuracy and the context needed in production environments. Taken together, this creates a powerful tailwind for Amplitude as we continue building a durable, scalable company that can unlock the next frontier in software. Over the years, we have intentionally expanded beyond core product analytics and into adjacent workflows. We have continued that work and acquired Infinegro, an AI-native marketing analytics startups that connects spends, behavior, and revenue impact. Infinegro brings strong AI-native engineering talent to Amplitude. This strengthens our platform as a system of context and expands our ability to bring acquisition, activation, and retention into one continuous feedback loop. Yesterday, we launched our global AI agents, specialized agents, and MCP. This represents the start of a fundamental shift in how teams work with their analytics data. Historically, analytics has required humans to do most of the heavy lifting, writing queries, building dashboards, monitoring changes, interpreting results, and then figuring out what to do next. That process does not scale in a world where teams are shipping faster and faster. AI agents change that model. Instead of asking questions one at a time, teams can now delegate work to agents that continuously analyze behavior, surface insights, and guide action. Our agents understand events, funnels, cohorts, experiments, session replay, and outcomes because they operate inside a context system specifically designed for them. Agents make life easier by doing the work that slows teams down today. That is very, very different from bolt-on AI tools from SaaS companies that sit outside the data and try to infer meaning after the fact. The best way to see this and understand this is to look at it in action. I want to show you a quick teaser video, and then I'm going to show you a demo of what we've released. Let's go ahead and roll the video.

The word of the year is SLOT. S-O-O-T.