Confluent, Inc.

Welcome to the Confluent third quarter 2025 earnings conference call. I'm Shane Z from Investor Relations, and I'm joined by Jay Krebs, co-founder and CEO, and Rohan Sivaram, CFO. During today's call, management will make forward-looking statements regarding our business, operations, market and product positioning, growth strategies, financial performance, and future prospects, including statements regarding our financial guidance for the fiscal fourth quarter of 2025 and fiscal year 2025. These forward-looking statements are subject to risks and uncertainties which could cause actual results to differ materially from those anticipated by these statements. Further information on risk factors that could cause actual results to differ is included in our most recent Form 10-Q filed with the SEC. We assume no obligation to update these statements after today's call except as required by law. Unless stated otherwise, certain financial measures used on today's call are expressed on a non-GAAP basis, and all comparisons are made on a year-over-year basis. We use these non-GAAP financial measures internally to facilitate analysis of financial and business trends and for internal planning and forecasting purposes. These non-GAAP financial measures have limitations and should not be considered in isolation from or as a substitute for financial information prepared in accordance with GAAP. A reconciliation between these GAAP and non-GAAP financial measures is included in our earnings press release and supplemental financials, which can be found on our IR website at investors.confluent.io. References to profitability on today's call refer to a non-GAAP operating margin unless stated otherwise. And with that, I'll hand the call over to Jay.

Thanks, Shane. Good afternoon, everyone, and welcome to our third quarter earnings call. We're joining from New Orleans, where in two days we'll host Current, the data streaming event where real-time data and AI come together. Turning to the quarterly results, we delivered a strong Q3, exceeding the high end of all guided metrics. Q3 subscription revenue grew 19% to $286 million, Confluent Cloud revenue grew 24% to $161 million, and non-gap operating margin expanded three percentage points to approximately 10%. This performance underscores strong consumption growth in our cloud business, the deepening commitment of our customers, and our disciplined focus on driving efficient, sustainable growth. Last quarter, we outlined two areas of focus in our go-to-market and several areas where we were doubling down on early success, all aimed at accelerating use case expansions and supporting the long-term growth trajectory of our cloud business. I'll give a brief update on each of these. The first area of focus was tightening field alignment to drive more use cases into production. As we shared last quarter, we saw strong momentum in late stage pipeline progression, a metric that tracks the dollar value of new use cases moving into production. That momentum continued in Q3 with more than 40% sequential growth and progressing late stage pipeline and accelerating pace of new use cases. This positions us for durable consumption growth and was a key driver of our cloud performance this quarter. In parallel, we continue to build momentum in expanding our large customer base, delivering the largest sequential net add in 100K plus ARR customer count in the past two years, along with continued acceleration in million dollar plus ARR customer growth. Together, these results underscore the depth of opportunity within new workloads and the continued strength of expansion among our large customers who are increasingly standardizing on our data streaming platform and relying on Confluent to meet their business needs. Our second focus area centered on accelerating the build out of our DSP specialist team to drive multi-product selling. We've previously highlighted Flink momentum in the first half of the year, and we're pleased to report another strong quarter with Q3 Flink ARR for Confluent Cloud growing more than 70% sequentially. Flink usage has continued to expand across our customer base. More than 1,000 customers used Flink during the quarter. Stream processing is key as it enables companies to act on data the moment it's created, turning information into real-time decisions and results. A great example of the power of our Flink offering is Siemens Healthineers, a global leader in medical technology with operations in more than 70 countries. The company develops imaging systems, lab diagnostics, and connected medical devices used by hospitals and clinics around the world. Behind these lifesaving technologies is a constant stream of data that determines equipment reliability, accuracy, and ultimately patient outcomes. But Siemens Healthineers was hindered by disconnected systems that isolated critical data in silos. Lengthy file transfers, manual handling, and periodic batch processing often delayed insights by weeks. These delays prevented timely action to improve equipment performance and product quality, so they turned to Confluent Cloud with fully managed Flink. With Confluent, Siemens Healthineers built a unified real-time data backbone that streams and processes millions of events from imaging, lab, and devices daily. Flink continuously filters, joins, and enriches these streams to deliver timely, trustworthy operational insights that help improve device reliability, manufacturing, quality, and consistency of diagnostic data across its installed base. This foundation now gives Siemens Healthineers real-time visibility and the agility to move faster as it advances digital and AI initiatives that enhance care delivery and improve patient outcomes worldwide. Next, our partner ecosystem continues to deliver strong results. As of Q3, partners sourced well over 25% of our new business over the last 12 months. This is a clear sign of the consistency and scale we're building through our established partner relationships, which are instrumental in broadening our footprint and driving customer expansion. Confluent was named a MongoDB Partner of the Year and served as an AWS Launch Partner for the new AI Agents and Tools category in the AWS marketplace, further strengthening our position at the center of real-time data and AI. Lastly, we remain as competitive as ever, replacing CSP streaming offerings. We have maintained a win rate well above 90%, with average deal size more than doubling over the past two quarters, all while continuing to increase our at-bats. This is made possible with multi-tenant Frank clusters, enterprise clusters, and WarpStream, which together have delivered a 4X increase in consumption of the past three quarters. Because of their multi-tenant architecture, we believe adoption of these new clusters is a tailwind to subscription gross margin over time. These differentiated offerings provide superior performance and lower TCO to our customers, which also helps us soak up more of the world's Kafka workloads. This includes one of the world's largest fintech companies who signed a seven-figure deal in Q3 to move their large-scale logging and telemetry workloads from open-source Kafka to Confluent. Another great example of this is Evobanco, a digital native bank in Spain serving hundreds of thousands of customers through its mobile-first platform. As transaction volume grew, its open-source Kafka clusters became increasingly difficult to scale and secure, with rising operational costs and downtime during peak loads. To address this, Evobanco migrated to Confluent Cloud as its central data backbone. The platform now streams and processes hundreds of thousands of financial events per day across payments, fraud detection, and customer channels. And with stream processing and fully managed connectors, Evobanco integrated core banking systems and analytics tools in real time without managing infrastructure. Since moving to Confluent, the bank has improved reliability, lowered costs, and accelerated the delivery of new banking features. Q3 also marked the one-year anniversary of our WarpStream acquisition. Over the past year, WarpStream has seen 8X growth in consumption, and we've closed multiple six-figure deals with marquee customers across different industries, including a Fortune 5 customer. We're encouraged by WarpStream's strong first-year performance and remain incredibly excited about this significant opportunity ahead. Next, I want to spend a few minutes on a key aspect of confluence opportunity in the AI space, providing context data for AI agents and applications. We're seeing a clear pattern across the industry. Many companies have shown they can successfully prototype AI, but fewer can get those systems into production. AI models are clearly capable, but a recent MIT study found that though enterprises are investing tens of billions of dollars in generative AI, most of these initiatives haven't delivered the desired results. The challenge isn't building a prototype. It's being able to build reliable business systems powered by AI that makes trustworthy decisions and takes appropriate actions. There are two factors that fundamentally drive the quality in AI systems, the model's capabilities and the data it has access to. Both of these are significant challenges, but they fall on different people to solve. Improving the quality of large-scale AI models is a challenge largely driven by a small number of LLM-producing research labs. Enterprises can easily harness the results of this work by simply pointing their apps at a new model. But getting data into shape to act as context for AI is a problem every enterprise must solve with their own data. This is where Confluent can help. One of the reasons AI demos are often so successful is because they can be powered by a one-time manually curated data set. But to take an agent to production, it must have an up-to-date, comprehensive view of all the inputs needed to do its work. This isn't just a matter of trying to hook the model into every source system directly. The source data is generally too messy and application-specific to lead to good results. And AI apps can't be spelunking around in production databases, reading through everything and potentially leaking the wrong data to the wrong user. That would be wildly expensive, create unsustainable production workloads, and be fundamentally insecure. Rather, the problem is about curating the right data for a given problem and creating a data set an agent can be tested with and evaluated against. Maintaining that live context is what determines how well an AI system performs. That's where accuracy, relevance, and trust are won or lost. What businesses need is a system that can keep data in motion so it can be processed, reprocessed, and served continuously as it changes. Our data streaming platform was built for exactly this problem. It works to connect data from every system, application, and cloud, and support just these kinds of complex pipelines. With Kafka, Flink, and TableFlow, teams can process in real-time, combining history and live events with one unified engine. When logic changes, you can go back and reprocess data to create the new data set. TableFlow and Flink work to combine the best aspects of real-time capabilities with the long-term historical store of data in the lake. As this goes out to production, the stream of feedback data can also be captured to measure the effectiveness of each change. And in two days, we will host Current and unveil new capabilities that are designed to make this even easier for customers and strengthen how our platform delivers real-time governed context. Confluence Data Streaming Platform is becoming the context layer for enterprise AI as businesses move from AI experimentation to production, from static data to living context, and from analysis to intelligent action. One customer that really illustrates this is a multi-billion dollar health and fitness chain with nearly 200 clubs and a rapidly growing digital platform. As the company expanded into AI-powered wellness, its data from wearables, class bookings, and mobile apps was siloed and processed in slow batches. This made it impossible to provide real-time personalized guidance through its GenAI companion. With Confluent Cloud as its streaming backbone, this customer now continuously ingests and enriches this data in motion. Wearable metrics, workout history, purchase activity, and engagement events are streamed and combined with contextual data, like recovery status or performance trends, before being routed into AI systems to fuel personalized recommendations. Confluent enables them to deliver AI insights in seconds instead of hours, scaling to millions of real-time interactions while enabling security and compliance. Fully managed infrastructure frees engineers to focus on innovation, helping the company turn decades of wellness expertise into intelligent, context-aware experiences that deepen member engagement and fuel digital growth. As AI evolves from innovation to utilization, context will define who wins, and we are committed to making Confluent the company enabling this shift by turning data into continuously refreshed, trustworthy context for AI systems everywhere. In closing, we're encouraged by the strong cloud consumption growth and the traction we're seeing for our complete data streaming platform, particularly with Flink. As AI becomes operational across every industry and geography, we believe that the demand for real-time context powered by data streaming will only grow. It's an exciting time for Confluent, and we're just getting started. With that, I'll turn it over to Rohan.

Thanks, Jay. Good afternoon, everyone, and thank you for joining our earnings call. Our strong third quarter performance highlights the momentum of our data streaming platform and our diversified growth strategy. We delivered strong top-line growth, stabilized our net retention rate, increased the adoption of new products, and drove continued margin expansion. These results demonstrate our ability to drive durable, profitable growth at scale over the long term. Turning to the results, Q3 subscription revenue grew 19% to $286.3 million and represented 96% of total revenue. Confluent platform revenue grew 14% to $125.4 million, driven by healthy demand in financial services. Cloud revenue grew 24% to 161 million, representing 56% of subscription revenue, compared to 54% in the year-ago quarter. We are pleased with our cloud performance this quarter, which was driven by stronger consumption across core streaming and DSP, including acceleration of new use cases moving into production. Turning to the geographical mix of total revenue, revenue from the US grew 13% to $172.1 million. Revenue from outside the US grew 29% to $126.4 million. Moving on to the rest of the income statement, I'll be referring to non-GAAP results unless otherwise stated. While driving top-line growth at scale, we continued to show significant operating leverage in our model. In Q3, subscription gross margin was 81.8% above our long-term target threshold of 80%. Operating margin increased 340 basis points to a record of 9.7%, exceeding our guidance by 270 basis points. This was driven by revenue outperformance and improved sales and marketing leverage from continuing to streamline coverage to drive growth. Adjusted free cash flow margin increased 450 basis points to 8.2%. Net income per share was 13 cents, using 370.6 million diluted weighted average shares outstanding. Fully diluted share count under the Treasury stock method was approximately 382.4 million. We ended the third quarter with 1.99 billion in cash, cash equivalents, and marketable securities, reflecting the strength of our balance sheet. Turning now to customer metrics, 20K plus ARR customer count increased to 2,533, up 36 customers sequentially. 100K plus ARR customer count was 1,487, up 48 customers quarter over quarter, representing the largest sequential increase in two years. New 100K plus ARR customers include many leading AI companies, such as Forbes 50 AI analytics provider, an AI-powered SIM cybersecurity vendor, a next-gen AI automation platform company. Our 100K plus ARR customers continue to account for more than 90% of our ARR. 1 million plus ARR customer count increased to 234, representing growth acceleration of 27%, driven by new use case expansion across cloud and platform. Additionally, more than 10 of the 15 net new 1 million plus ARR customers increased their spend on DSP products over the previous quarter. NRR for the quarter stabilized at 114%, while GRR remained close to 90%, driven by stronger consumption growth in our cloud business. Turning to our outlook, for the fiscal fourth quarter of 2025, we expect subscription revenue to be in the range of 295.5 to 296.5 million, representing growth of approximately 18%, non-GAAP operating margin to be approximately 7%, and non-GAAP net income per diluted share to be in the range of $0.09 to $0.10. For fiscal year 2025, we expect subscription revenue to be in the range of 1.1135 to 1.1145 billion, representing growth of approximately 21%. Non-GAAP operating margin to be approximately 7%. Non-GAAP net income per diluted share to be in the range of 39 cents to 40 cents. And adjusted free cash flow margin to be approximately 6%. For modeling purposes, we expect Q4 cloud revenue to be approximately $165 million, representing growth of approximately 20% and accounting for approximately 56% of subscription revenue based on the midpoint of our guide. Turning to the key drivers of our business, we saw strong demand in our core streaming business and good momentum across DSP AI and our partner ecosystem. First, our continued focus on field alignment is delivering strong results. In Q3, we accelerated the pace of moving new use cases into production and sustained strong momentum in building our late-stage pipeline, which once again grew more than 40% sequentially. We're also seeing customers commit to larger and longer-term deals, reflected in RPO growth of 43%, another quarter of acceleration. Together, these trends give us greater visibility into near-term consumption revenue and increase longer-term visibility with improved RPO to revenue coverage. Second, we saw good DSP momentum across cloud and on-prem in Q3. Building on the momentum from the first half of the year, we delivered another quarter of strong performance for Flink with particular strength in cloud. Q3 Flink ARR for Confluent Cloud grew more than 70% sequentially, and we now have more than 1,000 Flink customers, including more than a dozen customers with greater than 100K in Flink ARR and four customers with greater than 1 million in Flink ARR. This comprehensive breadth and depth represents the foundation for scaling into a very significant Flink market opportunity ahead. Here are two customer examples to illustrate how Flink begins to drive ARR expansion in our customer base. These customers are spending currently north of $100K plus and $1 million plus Flink ARR, respectively. Notably, in the last year alone, adoption of Flink has supported both customers to more than 6x their total spend. Third, we are strongly positioned to deliver contextualized, well-governed, and AI-ready data to companies. We now have more than 100 AI-native customers, including 21 with 100k plus in ARR, demonstrating Confluent's highly strategic role in the age of AI. Fourth, we are pleased with seeing continued traction in our partner ecosystem. On a trailing 12-month basis, Q3 partner-sourced deals increased to more than 25% of our new business, up from more than 20% last quarter. As we grow beyond the billion-plus revenue scale, we expect partners to play an even bigger role in driving growth and leverage in our business in the years ahead. Lastly, we've continued to demonstrate the effectiveness of our disciplined ROI-driven capital allocation strategy, especially in M&A. Q3 marked the one-year anniversary of our WarpStream acquisition. And in just one year, WarpStream's consumption has grown nearly eightfold. Following the Emmerich acquisition, we shipped our Flink product in spring of last year. And since then, we've scaled Flink into a low eight-figure ARR business. The strong financial performance underscores the successful path both products are on and reinforces the strength of our overall capital allocation strategy. In closing, we delivered strong third quarter results, demonstrating durable top line growth and margin expansion at scale. We are encouraged by the strong consumption growth in our cloud business and remain focused on continuing to execute on our key growth drivers across core streaming, DSP, AI, and the partner ecosystem. Looking forward, we believe we are well positioned to take advantage of the large market opportunity ahead. Now, Jay and I will take your questions.