Confluent, Inc.

Welcome to the Confluent Q4 and Fiscal Year 2024 Earnings Conference Call. I'm Shengzi from Investor Relations, and I'm joined by Jay Kreps, co-founder and CEO, and Rohan Sivaram, CFO. During today's call, management will make following statements regarding our business, operations, sales strategy, market and product positioning, strategic partnerships, financial performance, and future prospects, including statements regarding our financial guidance for the fiscal first quarter of 2025 and and fiscal year 2025. These following 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 fund thank you file 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 an earnings-based lease and supplemental financials, which can be found on our IO website at investors.confluent.io. References to profitability on today's call refer to non-GAO operating margin unless data otherwise. With that, I'll hand it over to Jay.

Thanks, Shane. Good afternoon, everyone, and welcome to our fourth quarter earnings call. I'm happy to report we exceeded all guided metrics. Subscription revenue grew 24% to $251 million. Confluent Cloud revenue grew 38% to $138 million. and non-gap operating margin was 5%, our third consecutive positive quarter. These results highlight our customers' need for a complete data streaming platform, our world-class innovation engine, and our successful transformation to a consumption-driven go-to-market model. I'm also thrilled to announce a major expansion of our strategic partnership with Databricks. This collaboration brings together Confluence's complete data streaming platform and Databricks' data intelligence platform to empower enterprises with real-time data for AI-driven decision-making. The bidirectional integration between Confluence TableFlow with Delta Lake and Databricks Unity Catalog will provide consistent real-time data across operational and analytical systems that is discoverable, secure, and trustworthy. Built on open standards, these integrations ensure real-time interoperability and flexibility across diverse ecosystems, seamlessly working with the tools and data infrastructure that companies already use. Operational data from Confluent becomes a first-class citizen in Databricks, and the insights created within Databricks can be driven back into any processor in the enterprise via TableFlow and Confluent. This is an incredibly exciting prospect for companies worldwide. This partnership extends TableFlow's reach across the analytics ecosystem, positioning Confluent as the leading vendor for delivering data across the enterprise. This is crucial for scaling AI innovation by giving application developers, data engineers, data analysts, and data scientists a single real-time source of truth to power advanced analytics and next-gen AI-driven applications. Additionally, our partnership with Databricks includes comprehensive go-to-market efforts encompassing field and partner enablement, solutions architectures, co-marketing, and co-selling initiatives. Together, we will enable businesses to harness the power of real-time data to build sophisticated AI-driven applications for their most critical use cases. TableFlow continues to be one of the most exciting and powerful additions to our data streaming platforms. TableFlow exposes Confluent's data streams as continuously updating tables in cloud object storage using open standards like Apache Iceberg, now Delta Lake. This allows Confluent to act as the bridge between operational systems that run the business and analytical platforms like Athena, BigQuery, Databricks, and Snowflake that extract valuable insights. Historically, operational and analytical systems operated in separate silos, managed by different teams and composed of different technologies and workflows. To compensate, teams built point-to-point batch-oriented pipelines to move operational data to the analytical estate, resulting in insights based on outdated and incomplete data. In the era of real-time data and AI, stale data simply isn't enough for modern businesses. Data streaming has emerged as a major data platform, putting Confluent in a unique position to replace the brittle connections between operations and analytics with something that is much more robust and much more scalable. In fact, our mission and business model is built on creating continuous trustworthy and discoverable streams of data that can be consumed anywhere in the organization. TableFlow further realizes our mission by making real-time consistent and secure data available as structured tables in cloud object storage using an open table format. With TableFlow, data is defined and stored once, but accessible across multiple processors, breaking down silos and enabling faster, more accurate insights. TableFlow was met with excitement across our customer base and is already delivering real benefits to early customers. Take a U.S. digital native customer that simplifies bookings and operations for ground transportation companies across three continents as an example. Their customers require real-time data for a seamless online booking experience with accurate pricing and precise arrival and drop-off times. Previously, they did this by loading data into Snowflake with batch jobs for analytics. However, this caused delays and increased data processing costs. So the digital native customer implemented TableFlow as part of our early access program to bridge their operational data with their analytic systems using Apache Iceberg. With TableFlow, Confluent Cloud automatically performs the required data pre-processing and ingests it into Snowflake as high-quality data. The customer can now derive business insights directly from the data faster and at a much lower cost, significantly speeding up analysis and decision-making for its transportation customers. TableFlow is also a great example of what we discussed last quarter. Our third wave of growth will come from being a complete data streaming platform. Over the last year, we continued to see strong DSP momentum in our cloud. Connect, process, and govern accounted for approximately 13% of our cloud business, with consumption growing substantially faster than overall cloud. No other vendor is as intensely focused as us on building and delivering a complete data streaming platform that connects streams, processes, and governs data continuously in motion. This puts Confluent in a highly advantageous position because over time, as more parts of our platform are used, a virtuous cycle of adoption drives stickiness and more growth. Above all else, we believe a complete data streaming platform solves our customers' hardest problems, reduces complexity, and provides substantial ROI. Let me walk through a few customer examples. Zazzle is a global online marketplace and platform for creating and customizing unique designs. The company is built on a foundation of technological innovation that connects customers, creators, and makers, powering the creation of almost anything. As a leading global marketplace, Zazzle needs to efficiently process massive amounts of clickstream data to deliver personalized experiences across its unparalleled range of products and designs. With hundreds of thousands of independent creators making a living through the Zazzle platform, and customers in every country worldwide maintaining platform performance while eliminating redundant data became critical. So Zazzle implemented Confluence's fully managed Flink offering to transform their largest data pipeline. By shifting stream processing earlier in the pipeline before writing to Google BigQuery, Zazzle reduced storage and computation costs while delivering more relevant product recommendations, directly impacting revenue. But this is just the start. With this foundation in place, Zazzle plans to expand their Flink usage to additional data streams to further enhance real-time personalization capabilities. A leading European grocery delivery service has also built its data architecture on Confluence data streaming platform and leverages our Apache Flink offering to optimize real-time order management. This digital-first company manages the entire grocery delivery process, overseeing daily inventory updates for thousands of products across local warehouses. To meet their ambitious promise of delivery within 20 minutes, they require a robust real-time stream processing solution to monitor and manage orders end-to-end, from warehouse to driver to customer. Previously, their reliance on REST API calls and event-driven architectures using open-source Kafka led to inefficiencies, delays, and fragmented data sources. By transitioning to Confluent Cloud with Apache Flink, they now seamlessly process key data streams, including grocery orders and warehouse locations, into a unified order topic that is easy to manage and consume. Flink further enables them to aggregate orders, assign them to delivery drivers, and track driver speed and location to provide accurate delivery time estimates for customers. This streamlined solution has significantly enhanced their order management capabilities, resulting in reduced development costs, minimized downtime, and a faster, more seamless experience for both drivers and customers. A top three Fortune Global 100 telecom customer shows the value of a complete DSP. As consumers make calls, send texts, and access the internet, a constant flow of data from mobile devices is sent to cell towers across the network. This data then needs to be shared with partners and subsidiaries in real-time so they can optimize network coverage and analyze customer usage patterns. The telco's previous legacy streaming service was unable to deliver the scale and speed required for the mission-critical cell tower workloads. So they turned to Confluence Complete DSP for real-time visibility and improved scalability across their wireless network. With Confluence data streaming platform, the telecom provider streams mobile data from 70,000 U.S. cell towers with connectors feeding data into lakes and warehouses. Stream processing provides real-time insights into network reliability and performance of mobile devices and wireless plans, which is then shared with partners and subsidiaries. This allows the telecom provider to unlock new revenue streams by making faster, smarter decisions, ranging from where to invest in 5G capabilities to where to lay down fiber optic cables. Citizens Bank, one of America's oldest and largest financial institutions, transitioned from open source Kafka to Confluent DSP to strengthen its digital banking offerings. Today's banking customers expect real-time experiences like immediate fraud alerts and instant access to deposited funds. But with an expanding data footprint, citizens struggled self-managing open source Kafka, which required 20 full-time employees just to support. So they turned to Confluent's complete data streaming platform. Using Confluent Cloud, Citizens Bank connects data from sources like consumer checking account, credit cards, and FICO fraud scores, generating real-time actionable insights. Stream governance ensures the bank's data is high quality and trustworthy by using schemas to reduce data inconsistencies and ensure compliance. With Confluent, Citizens Bank has reduced IT costs by 30% and saved $1.2 million annually by reducing fraud false positives by 15%. Additionally, the bank has seen a 20% increase in customer engagement, a 40% faster loan processing time, and a 10-point increase in net promoter score from improved customer interactions. And finally, I'd like to close with an update on the innovation and momentum in our Kafka business, including wins in early WarpStream success. At Confluent, our strategy starts with capturing the vast opportunity presented by Apache Kafka, which serves as the real-time backbone for more than 150,000 organizations worldwide. Doing this requires having the right offering to meet the performance, TCO, and reliability requirements of an incredibly wide variety of use cases. In 2024, we invested in offerings to better capture the entirety of this market. One area we targeted was the high-volume, cost-sensitive workloads common in observability, analytics, security, and IoT. Now generally available, freight clusters are a great offering for this segment. They're designed to attract cost-conscious customers with high-throughput, latency-tolerant workloads. We paired this with WarpStream, which serves a similar customer base but allows running directly in the customer's account, adding a low-friction midpoint between self-managed and SaaS. We've seen great traction with both of these offerings in helping us penetrate new accounts, particularly in the large-scale digital native segment with offerings that address use cases that demand zero access security and have tolerance for relaxed latency. This is playing out already. In fact, every WarpStream deal closed since acquisition was from our digital native cohort, including companies like Elastic, the search AI company used by over half the Fortune 500, and Cursor, the AI code editor that's become one of the hottest names in AI. And the vast majority are net new customers to Confluent. We're excited for the future of WarpStream and continue to invest in its innovation, including a whole host of new features released in January. One expansion with WarpStream this quarter was with a digital native customer that helps developers access real-time data. Their large-scale and high storage requirements made this a significant cost driver. Previously, they used Red Panda, but as their usage increased, so did their bill. The unsustainable costs combined with performance issues with Red Panda led to their decision to adopt WarpStream. Switching from Red Panda to WarpStream delivered immediate benefits for the customer, including nearly 10x cost savings and the ability to handle much higher data volumes on their platform. This has unlocked entirely new use cases for the customer that weren't possible before. In closing, we're pleased with our strong performance this year. The progress we made and the innovation we delivered to customers in 2024 set us up to capture more of the significant market opportunity ahead. With that, I'll turn it over to Rohan.

Thanks, Jay. Good afternoon, everyone, and thank you for joining our earnings call. We had a strong finish to fiscal year 2024, delivering durable growth, significant operating leverage, and positive free cash flow. In fiscal year 2024, subscription revenue grew 26% to $922.1 million and non-GAAP operating margin improved 10 percentage points to 2.9%, and free cash flow margin improved 17 percentage points to 1%, making fiscal year 2024 our first non-GAAP profitable year in the company's history. These results well exceeded our initial expectations across all guided metrics entering the year, reflecting the power of our data streaming platform and our team's excellent execution against our large market opportunity. Turning to the Q4 results, subscription revenue grew 24% to $250.6 million, exceeding the high end of our guidance and representing 96% of total revenue. Confluent platform revenue grew 10% to $112.7 million and accounted for 45% of subscription revenue. Demand for enterprise-grade data streaming in regulated industries remain a key growth driver for Confluent platforms. Confluent Cloud revenue grew 38% to 137.9 million and accounted for 55% of subscription revenue compared to 49% a year ago. During the quarter, we saw stable consumption and continued use case expansion across our large customer base, driving robust growth in our core streaming business. Additionally, we saw continued adoption of new components of our data streaming platform. DSP cloud consumption, which includes connect, process, and govern grew substantially faster than overall cloud and accounted for approximately 13% of our cloud business. Turning to geographical mix of total revenue, revenue from the U.S. grew 20% to 153.7 million. Revenue growth from outside the U.S. accelerated to 26% and was 107.5 million. Earlier today, we announced a multi-year strategic partnership with Geo Platforms Limited, an Indian multinational technology company and a subsidiary of Reliance Industries Limited. By making Confluent Cloud available on Geo Cloud services and Confluent Platform as a managed service, the partnership is expected to accelerate India's development of Gen AI and next-gen applications, delivering the power of real-time data to more businesses in the country. Moving on to rest of the income statement, I'll be referring to non-GAAP results unless stated otherwise. While continuing to drive top-line growth at scale, we once again demonstrated significant operating leverage in our model. In Q4, subscription gross margin increased 90 basis points to 82%, primarily driven by the economies of scale in Confluent Cloud. Operating margin was 5.2%, exceeding our guidance of approximately 2%, and was primarily driven by revenue and gross margin outperformance. Pre-cash flow margin expanded approximately 8 percentage points to reach a record high of 11.1%. Net income per share was $0.09, using 362.1 million diluted weighted average shares outstanding. Fully diluted share count under the treasury stock method was approximately 370.1 million. Net income per share was $0.09, using 362.1 million diluted weighted average shares outstanding. Fully diluted share count under the treasury stock method was approximately 370.1 million. And our balance sheet remains strong, ending the fourth quarter with $1.91 billion in cash, cash equivalents, and marketable securities. Turning now to other business metrics. Q4 win rate for new business once again saw a notable increase both year over year and sequentially. Our win rate against the CSP offerings and smaller startups remained well above 90%. This underscores the strength of our complete data streaming platform, providing outstanding performance with unparalleled reliability and flexibility and favorable TCO and ROI for our customers. This coupled with our consumption transformation has driven a year of high velocity land and expand. We ended fiscal year 24 with approximately 5,800 customers, representing an increase of 840 customers, nearly double the total increase from the previous year. New customers in the quarter include a top five video gaming company, one of the world's largest sports media outlets, a Fortune 100 pharmaceuticals company, a global cruise operator, a leading European airliner, and many more. We also drove robust expansion in our large customer base. We grew our 100K plus ARR customer count to 1,381, an increase of 12% from a year ago. This represents approximately 24% of our total customers, a key success indicator of our expansion strategy after landing a customer. These 100K plus ARR customers represented approximately 90% of our revenue, Our 1 million plus ARR customers grew even faster, accelerating to 23% and ending the quarter at 194 customers. New 1 million plus ARR customers include customers from a wide variety of industries spanning financial services, healthcare, manufacturing and logistics, retail, technology and more. Q4 NRR was 117% while GRR remained above 90%. Our stabilized NRR in recent quarters coupled with continued strength in GRR provides a solid foundation for delivering on our growth target this year. Before turning to our guidance, I would like to discuss Confluence positioning for 2025 and beyond. 2024 was in many ways a consequential year. First, we have optimized our pricing and packaging with the introduction of enterprise clusters, FRIT clusters, and the acquisition of WarpStream. This has significantly increased our serviceable addressable market as we are positioned to deliver best-in-class TCO for a broad range of use cases across self-managed, fully managed, and BYOC deployment models. Second, we extended our technology lead by expanding our DSP capabilities with more than 200 features and capabilities across stream, connect, process, and govern. With the upcoming TableFlow GA release, we will expand our growth vector by unifying the operational and analytical estates in data management. Finally, we have successfully transitioned to the next generation go-to-market model, focusing our team on consumption-based selling. By increasing consumption of our data streaming platform, we help customers realize substantial ROI for powering their mission-critical and real-time AI workloads. As we drive ROI-based expansions throughout our customers' data streaming journey, we expect our growth and profitability profile to strengthen over time. Following a year of substantial transformation, we have established a major data platform for the enterprise, unlocking the power of data streaming for thousands of customers and operating at a $1 billion plus revenue run rate. Given the strong foundation we set last year, we expect to begin reaping the benefits in 2025. Our objective is to continue soaking up the world's Kafka and to establish 2025 as the year of DSP. We will support these initiatives with a resource allocation strategy focusing on efficient growth and prioritizing our investments in expanding our DSP capabilities, hiring and enabling our team to sell DSP, and forming strategic partnerships and alliances. We look forward to driving durable and efficient growth in 2025 as we execute against our large and growing market opportunity. Now let's turn to our guidance. we are providing Q1 and fiscal year 2025 subscription revenue outlook ahead of expectations. In addition to guiding fiscal year 2025 non-GAAP operating margin within our midterm target set at the time of our IPO. For the first fiscal quarter of 2025, we expect subscription revenue to be in the range of 253 to 254 million, representing growth of approximately 22 to 23%. Non-GAAP operating margin to be approximately 3%. and non-GAAP net income per diluted share to be in the range of $0.06 to $0.07. For fiscal year 2025, we expect subscription revenue to be in the range of $1.117 to $1.121 billion, representing growth of approximately 21% to 22%. Non-GAAP operating margin to be approximately 6%, and non-GAAP net income per diluted share to be approximately $0.35. I'd also like to provide a few modeling points. For subscription revenue seasonality, at the midpoint of our guidance, we expect the first half of fiscal year 2025 will be approximately 46.5% in line with the average of the first half seasonality in the last two years. For cloud revenue, we are comfortable with the current consensus dollar estimate for fiscal year 2025, and we expect to see approximately one point of increase in cloud subscription revenue mix each quarter with a Q4-25 exit of approximately 59 to 60%. For free cash flow margin, we expect a one-time negative impact of approximately 15 points to Q1-25 or approximately three to four points to fiscal year 2025, resulting from a change to timing of cash compensation payments for most of our non-go-to-market employees. Excluding this one-time impact, we expect adjusted free cash flow margin for fiscal year 2025 to be approximately 6%. In closing, a strong finish to 2024 is a testament to our large TAM, the market leadership of our technology platform, and our world-class team. Powered by the secular tailwinds of cloud, data, and AI, we are incredibly excited to take advantage of the market opportunity ahead. Before turning to Q&A, we will host Investor Day 2025 on March 6th in San Francisco. If you are interested in attending in person, please contact the IR team at investors at concluent.io. Now, Jay and I will take your questions. Thanks, Rohan.