Good afternoon, everyone, and welcome to Amplitude's Third Quarter 2025 Earnings Call. Today, I'm going to cover 3 things: first, our strong Q3 results and progress in the enterprise; second, the AI opportunity within analytics; third, product innovation and our customers. Let's go ahead and get started with our Q3 results. We delivered another strong quarter, continuing the acceleration we saw in Q2. We exceeded expectations on our core financial metrics and made solid progress against our enterprise strategy. Our third quarter revenue was $88.6 million, up 18% year-over-year and exceeding the high end of our guidance. Annual recurring revenue was $347 million, up 16% year-over-year and up $12 million from last quarter. Non-GAAP operating income was $0.6 million. Customers with more than $100,000 in ARR grew to 653, an increase of 15% year-over-year. Our Q3 performance reflects our continued execution against our strategy. We are winning simple by bringing Amplitude to everyone with AI. We are winning the enterprise with broad-based success with both AI natives and traditional enterprises, securing larger multi-year contracts. And we're winning the category with multi-product adoption now representing 71% of our ARR. Finally, we're winning together by leading the shift to being AI native across the entire Amplitude team. I wanted to take a little bit of time to talk about how AI is changing how software gets built. Every single product team runs the same loop: build, ship, use and learn. The left side of that loop, build and ship, has been transformed by AI. AI coding has made it faster than ever to turn ideas into products. We are now at a point where someone can create a product that's used by millions overnight. By contrast, the right side of this loop, use and learn, remains in the stone ages. Companies ask users what they want, but actions are more powerful than words. The best way to understand what people want is to watch what they do. This is what Amplitude solves. Our AI analytics platform helps companies understand how people engage in their product, what they like, where they get stuck and what keeps them coming back. These behavioral signals are the most powerful indicator for what to build. Automating and scaling that understanding is the next frontier. In this context, analytics is the perfect problem for AI to solve. To use analytics, you have to do a lot of manual work in specifying and setting up your query in between rounds of thinking. AI can handle all of that manual work, freeing up humans to focus on the thinking that leads to great insights. Amplitude has a unique position to build the AI analytics platform of the future. We have the world's largest database of product behavior. We have spent a decade working with world-class analytics teams. Over the past year, we've rebuilt the Amplitude team to be AI native. We've reorganized product development twice, and we've acquired 4 AI companies. We've trained our engineering, product management and design teams deeply in AI. The company that disrupts the right side of this loop, the use and learn, the fastest will define the future of this space. We are all in here. Let's get into the details on product innovation. In the last few weeks, we have launched several AI-native products here at Amplitude. I want to start with MCP. In October, we announced the public availability of our MCP server, the top requested feature from our customers. MCP is made for data analytics. It exposes all of Amplitude's functionality, so an AI agent can interact with it directly. It allows you to use Amplitude without knowing anything about the Amplitude UI or your data taxonomy. This is the best MCP use case that I have ever seen. Watching an AI agent think, reason, query Amplitude and then repeat that process iteratively is magical. It shows what is possible in the AI analytics future I talked about earlier. It brings the power of our data to anyone in any workflow. This opens Amplitude up to an entirely new cohort of nontechnical users, in turn driving our growth. Let me show you with a quick demo. MCP lets AI tools interact directly with Amplitude data. You can ask a vague question about your product inside any AI model and have a query Amplitude iteratively. Our MCP already has native connections to Claude, Cursor and GitHub with more to come soon. For this demo, I'm going to use Claude. I'm going to start with a simple prompt, give me high-level web traffic metrics. Claude will then get contacts, search web traffic metrics and then it's identified that during the week of September 21, we've had a peak. I can then ask follow-up questions to drill down, investigate the September spike. What's driving this growth? Claude then accesses behavioral insights, checks traffic sources, marketing campaigns and content performance. It shows that our webinar campaigns and the release of our product benchmark report drove this traffic. To get deeper insights, I'm going to ask, what are the downstream growth metric impacts by these campaigns? Claude then queries the campaign data set, downstream conversion funnels and sales force metrics. It concludes that the September campaigns drove a higher number and quality of visitors to the site. Of course, I'm going to want to share these findings so I can prompt it to create an Amplitude notebook for the growth team. So in a few minutes, customers can get deep research, insights and a detailed shareable notebook that allows them to take action. In addition to the launch of MCP, we expanded the open beta for our AI agents. These agents continually monitor product data, detect anomalies and surface insights automatically. In June, we launched our closed beta. And then 2 weeks ago, we opened the beta to all customers. Our focus is now on 2 agents. The first is the Dashboard Agent, which analyzes charts and proactively flag significant changes. And the second is the Session Replay Agent, which reviews thousands of user sessions, detects points of friction and then shows curated clips that highlight issues. Both are powered by the same behavioral data that MCP can access. They are already helping customers uncover opportunities and resolve issues faster. In addition, last week, we also introduced AI Visibility. As consumers turn to AI tools like ChatGPT, Claude and Google's AI summary when they search, marketers are flying blind. They have no idea how their companies show up or rank within the results produced by these new tools. To solve that problem, we launched AI Visibility for free last week. Think of it as SEO for LLMs. It shows where a brand appears or doesn't across all major AI models, how they rank against competitors and how they can improve their position. We saw a lot of excitement around the launch with our customers and on social media. The conversation about the future of AI Visibility is still going today on Twitter. Let me show you a quick demo of this, too. Understanding how your products appear in AI responses and improving it will be the key to increasing awareness. With AI Visibility, customers can now see the percentage of mentions of their product and AI responses. They can also see competitor mentions versus their own and then topics by visibility. They can dig into prompts to see the exact questions customers are asking and how AI is answering. For example, when people ask LLMs for product-led growth tools, they mention Amplitude 90% of the time. Customers can also learn how to improve their ranking. I can use the Analyze page to see how AI interprets the existing content or run a series of simulated changes to test updates before publishing. AI Visibility tracks your brand and helps you turn that visibility into growth. Finally, next week, we will launch AI Feedback. This is our newest AI-native product based on the core offering from our Kraftful acquisition in July. We're going from acquisition to new Amplitude product launch in 4 months. AI Feedback takes user feedback and information from multiple sources and turns it into insights a company can use. By bringing feedback, behavior and action into a single platform, it helps teams hear customers and understand them. Let me show you with my last demo. AI Feedback is the new way to listen to users at scale and act on their feedback. AI Feedback collects input from all of our customers' feedback sources. You can link