Q1 2024 Confluent Inc Earnings Call

Shane Xie: Hello, everyone. Welcome to the Confluent Q1 2024 Earnings Conference Call. I'm Shane Xie 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 four forward-looking statements regarding our business, operations, sales strategy, market, and product positioning, financial performance, and future prospects, including statements regarding our financial guidance for the fiscal second quarter of 2024 and fiscal year 2024. These following statements are subject to risks and uncertainties, which could cause actual results that differ materially from those anticipated by these statements.

Hello, everyone and welcome to the <unk> Q1, 'twenty 'twenty four earnings conference call I'm, Shane Z from Investor Relations and I'm joined by Jay Crabs, co founder and CEO and <unk> <unk> CFO.

Shane Xie: Further information on risk factors that could cause actual results to differ is included in our most recent Form 10-K filed with the SEC. We assume no obligation to update these forward-looking statements after today's call, except as required by law. Unless data otherwise indicates, certain financial measures used on today's call are expressed on a non-gap basis, and all comparisons are made on a year over year basis. We use these non-gap 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 considered in isolation from, or as a substitute for, financial information prepared in accordance with GAAP.

Shane Xie: 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 IO website at investors.confluent.io. And finally, once we have concluded our earnings call, we will post the Confluent Earnings Report on our IO website. The report is a single PDF that contains our earnings infographic, one-pagers on our technology, our prepared remarks, and slides from today's earnings call. Going forward, we plan on publishing the report at the end of our quarterly earnings call. With that, I'll turn it over to Jay. Thanks, Shane.

During today's call management will make forward looking statements regarding our business operations sales strategy market and product positioning financial performance and future prospects, including statements regarding our financial guidance for the fiscal second quarter of 2024 and fiscal year 2020 for.

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-K 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 our financial and business trends and for internal planning and forecasting purposes. These non-GAAP finance.

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 thought confluent that.

And finally once we have concluded our earnings call. We will post the confluent earnings report to our IR website.

The report is a single PDF, which contains our earnings infographic, one pagers on our technology, our prepared remarks and slides from today's earnings call going forward. We plan on publishing the report at the end of our quarterly earnings call.

That I will turn the call over to Jay.

Unknown Attendee: Thanks, Shane. Good afternoon, everyone, and welcome to our first quarter earnings call. I'm happy to report we had a strong start to the year, exceeding the high end of all guided measures. Total revenue grew 25% to $217 million. Confluent cloud revenue grew 45% to $107 million, which now accounts for the majority of our subscription revenue and remains our fastest growing offer. Non-Gap Operating Margin improved 22 percentage points, our fourth consecutive quarter of more than 20 percent improvement.

Jay: Thanks, Sean and good afternoon, everyone and welcome to our first quarter earnings call I'm Happy to report, we had a strong start to the year exceeding the high end the bulk added metrics.

Jay Crabs: Total revenue grew 25% to $217 million confluent cloud revenue grew 45% to $107 million, which now accounts for the majority of our subscription revenue and remains our fastest growing offerings non-GAAP operating margin improved 22 percentage points, our fourth consecutive quarter of more than 20 points improvement. These results.

Unknown Attendee: These results reflect our team's strong execution amid a still uncertain but stabilizing macro environment. In Q1, we launched our consumption transformation. We oriented our sales compensation for cloud towards incremental consumption and new logo acquisition. We rolled out new systems, metrics, and measures and made pricing adjustments to reduce friction and land new customers. It remains early days, but we are encouraged by the strong promising signals of our consumption orientation, particularly around new customer acquisition and stabilization of consumption trends.

Jay Crabs: <unk> reflect our team's strong execution amid a still uncertain, but stabilizing macro environment.

Jay Crabs: Q1, we launched our consumption transformation, we've oriented our sales compensation for cloud towards incremental consumption and new logo acquisition, we rolled out new systems metrics and measures and made pricing adjustments reduced friction in landing new customers. It remains early days, but we are encouraged by the strong promising signals of our consumption orientation.

Jay Crabs: Particularly around new customer acquisition and stabilization of consumption trends with an increased focus on new logo growth. We added 160 customers to our total customer count our largest sequential growth since Q1, 'twenty three we not only increased the volume of customer additions, but we're better able to target high potential customers increase.

Unknown Attendee: With an increased focus on new logo growth, we added 160 customers to our total customer count, our largest sequential growth since Q1 2023. We not only increased the volume of customer additions, but we're better able to target high-potential customers, increasing the quality of our customer ads as well. We recently hosted Kafka Summit in London and Bangalore. Kafka Summit Bangalore was the first ever Kafka Summit in APAC.

Jay Crabs: The quality of our customer adds as well.

Jay Crabs: We recently hosted Kafka summit in London in Bangalore, Kafka Summit, Bangalore was the first ever Kafka summit in APAC. These events are a great illustration of the tremendous growth in innovation happening within the data streaming category between the two events, we had more than 7000 people joining us in person or registering virtually spanning startups enterprises and everything in between.

Unknown Attendee: These events are a great illustration of the tremendous growth and innovation happening within the data streaming category. Between the two events, we had more than 7,000 people joining us in person or registered virtually, spanning startups, enterprises, and everything in between, including organizations like Apple, Bloomberg, CERN, ING, Stripe, Uber, and many others. Our relentless pace of product innovation was on full display, with 15 major customer-facing features and price and performance optimizations announced across both events, including the general availability of Flink and early availability of a powerful new feature we call TableFlip.

Jay: Including organizations like Apple Bloomberg, CERN, IMG stripe Uber and many others.

Jay: A relentless pace of product innovation was on full display with 15 major customer facing features and pricing performance optimizations announced across both events, including the general availability of flink in early availability of a powerful new feature we call table as well.

Unknown Attendee: TableFlow makes all the data streams that flow through Confluent Cloud available as structured tables in cloud object storage using an open table format called Apache Iceberg. Let me provide a little background on what this means and why it's so powerful.

Jay: Tampa flow mix, all the data streams that flow through consequent cloud available in structuring tables and cloud object storage using an open table format called Apache Iceberg, Let me provide a little background on what this means and why it's so powerful.

Unknown Attendee: Historically, data in the analytics and data warehousing world existed in closed systems that trapped their data inside a walled garden. As the complexity of the analytics world has grown, this has led to a mishmash of data warehouses, data lakes, AI products, and reporting systems. This created lots of value for technology vendors but created yet another data silo for the end user. However, over the last five years, a trend has emerged of standardizing around open data formats and metadata on top of cloud object storage. The rise of cheap cloud object storage like S3 means another path is possible.

Jay: Historically data and the analytics and data warehousing world is existing in closed system attracts their data inside a wildcard as the complexity of analytics royalties grown. This has led to a mishmash of data warehouses data lakes AI products and reporting systems. This grant and lots of value for technology vendors, but created yet another data silo for the end user.

Unknown Attendee: Instead of fragmenting data across various analytical systems, the tables of data can be shared across systems. Apache Iceberg has arisen as the de facto standard for these open analytic tables on top of cloud object storage. Iceberg is an open source project that has near universal support across open source systems like Apache Spark and Flink, as well as in the data warehousing and data lake world, including products like AWS Athena, Redshift, Google's BigQuery, and Snowflake.

Jay: However over the last five years a trend this emerged of standardizing around open data formats and metadata on top of cloud object storage.

Jay: The rise of cheap cloud object storage like S. III is another path as possible.

Jay: Set of fragmenting data across various analytical systems. The tables of data can be shared across systems Apache iceberg has risen as the de facto standard for these open analytic tables on top of cloud object storage Iceberg is an open source project that has near universal support across the open source systems like Apache spark and Frank as well.

Jay: The data warehousing and genomic house world, including products like AWS, Athena redshift, Google Big query and Snowflake.

Unknown Attendee: TableFlow is more than just a connector. Already, Kafka and Confluent are one of the most common feeds of data into the analytics system. But with TableFlow, we can make that integration far deeper. Quora, our cloud-native Kafka implementation, already heavily relies on Cloud Object Storage for storing the streams of data in Confluent Cloud. TableFlow means that we can open up these same streams directly as iceberg tables with the click of a button. This means data is defined a single time, stored a single time, and no complex mappings or translations are needed.

Jay: <unk> is more than just a connector already kafka confluence are one of the most common themes with data and analytics system, but with table flow, we can make that integration far deeper Cora our cloud native Kafka implementation already heavily relied on cloud object storage for storing the streams of data in console and cloud capable flow means that we can open up these same streams.

Jay: Directly is iceberg tables with the click of a button.

Jay: This means data as defined single time stored a single time.

Unknown Attendee: TableFlow is in early access now and taking on its first user. For some vendors, the rise of open data formats like Iceberg is perceived as a threat as it opens up data that was locked in a silo to an ecosystem of processing and analytics layers, letting vendors compete on a level playing field based on cost, performance, and features, rather than any new entrant having to overcome significant data gravity. However, we believe Confluent is uniquely positioned to benefit from this trend as our goal, and indeed our business model, is built around the sharing of data.

Jay: And Neil complex mappings, our translations are needed table flowers and early access now and taking on its first users.

Jay: For some vendors the rise of open data formats like iceberg is perceived as a threat as it opens up data that was locked in a silo to an ecosystem of processing and analytics layers letting vendors compete on a level playing field based on cost performance and features rather than any new entrants having to overcome significant data gravity. However.

Jay: However, we believe confluence is uniquely positioned to benefit from this trend as our goal and indeed, our business model is built around the sharing of data. So the rise of iceberg creates a very important destination for data that can increase the value of the streams on our platform. This makes table, who are central to confluence vision of opening up and connecting all the data in an organization we've heard Oh.

Unknown Attendee: So the rise of Iceberg creates a very important destination for data that can increase the value of the streams in our platform. This makes Tableflow central to Confluent's vision of opening up and connecting all the data in an organization. We've heard overwhelmingly positive feedback from customers on this announcement and look forward to making this a significant part of our business over time. Last quarter, we discussed the world of stream processing and why our Flink offering is uniquely positioned to win this market.

Jay: Well, mainly positive feedback from customers with this announcement and look forward to making this a significant part of our business over time.

Jay: Last quarter, we discussed the world of stream processing and wire flink offering is uniquely positioned to win this market and we have been seeing incredibly interesting excitement for our flank offering nearly 600 prospects and customers who tried flink such as preview our Kafka summit, London, We announced the general availability of confluence cloud for Apache flank early customer feedback has been strong we've seen that.

Unknown Attendee: And we've been seeing incredibly interesting excitement for our Flink offering. Nearly 600 prospects and customers have tried Flink since its preview. At Kafka Summit London, we announced the general availability of Confluent Cloud for Apache Flink, and early customer feedback has been strong.

Unknown Attendee: We see many of these customers starting the ramp towards production applications that will drive significant consumption over time. We announced another exciting Flink development at Kafka Summit Bangalore. We'll be adding Flink to our on-premise software offering, Confluent Platform. This helps our on-premises and hybrid customers adopt Flink for critical workloads running in their data center. These are very exciting steps for Confluent, and it cements our position as the only complete data streaming platform.

Jay: Any of these customers starting the ramp towards production applications that will drive significant consumption overtime, we announced another exciting flink developments at Kafka summit, Bangalore, we'll be adding linked to our on premise software offering confluent platform.

Jay: This helps our on premise and hybrid customers adopt link for critical workloads running in their data centers.

Jay: These are very exciting steps for confluence and it cements our position as the only complete data streaming platform cable flow and flank or new capabilities beyond Kafka and represents significant progress towards building. What we believe will be the most important data platform and a modern company <unk>.

Unknown Attendee: TableFlow and Flink are new capabilities beyond Kafka and represent significant progress towards building what we believe will be the most important data platform in a modern company. Gen AI continues to be top of mind for many companies, but most are coming to realize that LLMs don't stand alone. RAG, or Retrieval Augmented Generation, has emerged as the common pattern for Gen AI to extend the powerful LLM models to domain-specific datasets in a way that avoids hallucination and allows granular access control.

Jay: <unk> AI continues to be top of mind for many companies, but most are coming to realize that llm's don't standalone rag or retrieval augments and generation has emerged as the common pattern for gen. AI to extend the powerful LLM models to domain specific datasets in a way that avoids hallucination and allows granular access control industry.

Unknown Attendee: Data streaming platforms play a pivotal role in enriching RAG-enabled workloads with contextual and trustworthy data. They enable companies to tap into a continuous stream of real-time data from the systems that power the business and transform it into the right format to be used by vector databases for AI apps. Another announcement from Kafka Summit Bangalore that helps make this kind of RAG architecture easier with support for AI models and remote inference in Flink SQL.

Jay: And a streaming platforms play a pivotal role in enriching brag enabled workloads with contextual and trustworthy data. It enables companies to tap into a continuous stream of real time data from the systems the power of the business and transform it into the right format to be used by vector databases for AI applications.

Jay: Other announcement from Kafka summit, Bangalore that helps make this kind of rag architecture easier with support for AI models and remote inference in Flint sequel. This capability is designed to simplify the development and deployment of AI applications by enabling software developers to integrate inference and embedding computation directly into their data processing, making it easier than.

Unknown Attendee: This capability is designed to simplify the development and deployment of AI applications by enabling software developers to integrate inference and embedding computation directly into their data processing, making it easier than ever to bring AI to real-time apps. We're seeing particularly strong traction with Gen AI in the digital native segment, with companies like OpenAI, Notion, and Motiv, who are leveraging Gen AI to reimagine customer experiences in nearly every industry. One such customer is an AI-powered customer intelligence platform to manage contact centers and customer engagement.

Jay: Ever to bring AI to real time apps, we're seeing particularly strong traction with <unk> and the digital native segment with companies like open AI notion and motive, we're leveraging gen AI to reimagine customer experiences in nearly every industry.

Jay: One such customer is an AI powered customer intelligence platform to manage contact centers and customer engagements are powerful communications AI is central to its platform and is used for a variety of use cases, including servicing real time insights for call center managers and identifying when agents need immediate assistance or intervention and handling problematic situations there are existing.

Unknown Attendee: A powerful communications AI is central to its platform and is used for a variety of use cases, including surfacing real-time insights for call center managers and identifying when agents need immediate assistance or intervention in handling problematic situations. However, their existing architecture was unable to handle the demands of real-time, with latency sometimes exceeding a minute. This sluggishness was unacceptable for an AI application that requires access to fresh and continuously updated data.

Jay: Architecture was unable to handle the demands of real time with latency, sometimes exceeding a minute.

Jay: This sluggishness was unacceptable for an AI application that requires access to fresh and continuously updated data. So this customer turned to confluent cloud for fast and scalable data stream by integrating console with other components of its architecture. The customer was able to significantly reduce latency of spill response times from over a minute John to as low as 10 milliseconds.

Unknown Attendee: So this customer turned to Confluent Cloud for fast and scalable data streaming. By integrating Confluent with other components of its architecture, the customer was able to significantly reduce latency for response times from over a minute down to as low as 10 milliseconds. With faster, fresher data and more real-time insights available, the customer is better equipped to meet the needs of its customers and provide them with valuable tools and analytics for managing their contact centers and customer engagement.

Jay: With faster fresher data and more real time insights available to customers better equipped to meet the needs of its customers and provide them with valuable tools and analytics for managing their contact centers and customer engagements, but.

Unknown Attendee: But it's not just digital natives who are putting Gen AI into action. Another great example is GEP Worldwide, a global leader in supply chain and procurement solutions. This billion-dollar revenue company provides software, consultancy, and managed services to some of the world's biggest multinationals. Its software offerings are infused with GenAI to support chatbots and decision support tools. Previously, the team was an open-source Kafka shop, but operating and maintaining open-source became too burdensome to maintain, ultimately stifling their ability to iterate and innovate quickly. So they turned to Kafka.

Jay: But it's not just digital natives, who are putting gen AI into action. Another Great example, as GDP worldwide, a global leader in supply chain and procurement solutions.

Jay: This $1 billion revenue company provides software our consultancy and managed services to some of the world's biggest multinationals. It software offerings are infused by Gen AI to support chat bots and decision support tools previously the team was an open source Costco shop, but operating and maintaining open source became too burdensome to maintain ultimately stifling our ability.

Jay: To iterate and innovate quickly so they turned to confluence with confluence serving as the central nervous system of its software. The company is able to more quickly connect data across hundreds of applications, including those custom apps and the operational and analytical of states to provide contextual relevant and real time insights into its AI platform.

Rohan Sivaram: With Confluent serving as the central nervous system of its software, the company is able to more quickly connect data across hundreds of applications, including both custom apps and the operational and analytical estates, to provide contextual, relevant, and real-time insight into its AI platform. Confluent continues to innovate across its products and partner ecosystem to make it easier for customers so organizations can quickly scale and build AI-enabled applications using trusted data. In closing, I'm incredibly proud of our team.

Jay: Confluent continues to innovate across our products and partner ecosystem to make it easier for customers. So organizations can quickly scale and build AI enabled applications using trusted data streets.

Rohan Sivaram: Our rapid pace of innovation is phenomenal, and our field and go-to-market teams are leaning into our consumption transformation with early positive results. I've never been more excited or confident in Confluent's ability to capture the lion's share of the data streaming platform market. With that, I'll turn things over to Rohan.

Jay: In closing I'm incredibly proud of our team our rapid pace of innovation is phenomenal and our field and go to market teams are leaning into our consumption transformation with early positive results.

Jay: <unk> been more excited or confident in confluence ability to capture the lion's share of the data streaming platform market with that I'll turn things over to Ron.

Rohan Sivaram: Thanks, Jay. Good afternoon, everyone.

Ron: And good afternoon, everyone. We delivered solid first quarter results, beating all our guided metrics and uncertain macro environment key highlights include robust topline growth and bottom line improvements the largest sequential customer growth since Q1 2023.

Rohan Sivaram: We delivered solid first-quarter results, beating all our guided metrics in a still uncertain macro environment. Key highlights include robust top-line growth and bottom-line improvements, the largest sequential customer growth since Q1 2023, and great momentum in multi-product adoption. These results reflect our team's strong execution on our consumption transformation and our expanding multiproduct platform leadership and data streaming. Turning to the Q1 results, total revenue grew 25% to $217.2 million. Subscription revenue grew 29% to $206.9 million. Within subscription, Confluent platform revenue grew 15% to $100.1 million, representing 46% of total revenue. Customers rely on the Confluent platform to harness data streaming on-premises, on the edge, and bridge to the cloud.

Ron: <unk> momentum in multi product adoption.

Ron: These results reflect our team's strong execution on our consumption transformation and are expanding multi product platform leadership in investor day, turning to the Q1 results total revenue grew 25% to $217 2 million subscription revenue grew 29% to $206 9 million within.

Ron: Continent platform revenue grew 15% to $100 1 million, representing 46% of total revenue customers rely on confluent platform to harness data streaming on prem on the edge and bridge to the cloud we continue to see healthy demand for control platform as most organizations still early in their move.

Rohan Sivaram: We continue to see healthy demand for the Confluent platform, as most organizations are still early in their move to the cloud. Confluent cloud revenue grew 45% to $106.8 million, exceeding our guidance of $105 million, and ended the quarter at 49% of total revenue, compared to 42% a year ago. Our cloud performance was driven by the ramp in consumption from select customers added in recent quarters, and we started seeing stabilization of new use case expansion in our existing customer base, including our digital native segment. Turning to the geographical mix of revenue, revenue from the U.S. grew 23% to $127.4 million, and revenue from outside the U.S. grew 28% to $89.8 million.

Ron: The cloud confluence cloud revenue grew 45% to $106 8 million exceeding our guidance of $105 million and ended the quarter at 49% of total revenue compared to 42% a year ago. Our cloud performance was driven by the ramp in consumption from select customers added in recent quarters and.

Ron: We started seeing stabilization of new use case expansion in our existing customer base, including our digital media segment.

Ron: Turning to the geographical mix of revenue revenue from the U S grew 23% to $127 4 million revenue from outside the U S grew 28% to $89 8 million.

Rohan Sivaram: Moving on to the rest of the income statement, I'll be referring to non-GAAP results unless stated otherwise. Total gross margin was 76.9%, up 470 basis points. Subscription gross margin was 80.7%, up 320 basis points. We're pleased with operating above our long-term target level of 75% for total gross margin, even with a continued revenue makeshift to the cloud. Our cloud offering has significant architectural advantages in multi-tenancy, elasticity, data balancing, networking, and data replication.

Ron: Moving on to the rest of the income statement I'll be referring to non-GAAP results unless stated otherwise.

Ron: Gross margin was 76, 9% up 470 basis points subscription gross margin was 18, 7% up 320 basis points.

Ron: Pleased with operating above our long term target level of 75% for total gross margin, even with our continued revenue mix shift to cloud.

Ron: Our cloud offering has significant architectural advantages and multi tenancy elasticity data balancing networking and get our application combined with continued optimization every layer of the fact, we have driven a significant cost advantage and operations, while delivering industry, leading innovation to our customers at a lower <unk>.

Rohan Sivaram: Combined with continual optimizations at every layer of the stack, we have driven a significant cost advantage in operations while delivering industry-leading innovations to our customers at a lower DCO. Turning to profitability and cash flow, operating margin improved 22 percentage points to negative 1.5%, representing our seventh consecutive quarter of more than 10 points and fourth consecutive quarter of more than 20 points in margin improvement.

Ron: <unk>.

Ron: Turning to profitability and cash flow operating margin improved 22 percentage points to negative one 5%, representing our seventh consecutive quarter of more than 10 points and fourth consecutive quarter of more than 20 points of margin improvement operating margin performance was driven by our gross margin performance and <unk>.

Rohan Sivaram: Operating margin performance was driven by our gross margin performance and our continued focus on driving efficient growth across the company, with the most pronounced progress made in sales and marketing. The improvements in sales and marketing demonstrate focused efforts in driving operating leverage and improving unit economics. Net income per share was $0.05 for Q1 using 350.2 million diluted weighted average shares outstanding. The fully diluted share count under the treasury stock method was approximately 362.4 million.

Ron: Our continued focus on driving efficient growth across the company with the most pronounced progress made in sales and marketing the improvements in sales and marketing demonstrates focused efforts in driving operating leverage and improving unit economics.

Ron: Net income per share was <unk> <unk> for Q1, using $350 2 million diluted weighted average shares outstanding.

Ron: Fully diluted share count under the Treasury stock method was approximately $362 4 million.

Rohan Sivaram: Free cash flow margin improved 33 percentage points to negative 14.6%, and we ended the first quarter with $1.91 billion in cash, cash equivalents, and marketable security. Turning now to other business, the total customer count was approximately 5,120, representing an increase of 160 customers sequentially. This is our largest sequential growth in total customers since Q1 2023, reflecting the early signs of success from our consumption transformation. Customers with 100k plus in ARR grew 17% to 1,260 and continue to account for greater than 85% of our revenue.

Ron: Free cash flow margin improved 33 percentage points to negative 14, 6%.

Ron: And we ended the first quarter with $1 $91 billion in cash cash equivalents and marketable securities.

Speaker Change: Turning now to other business metrics.

Ron: Customer count was approximately 5120, representing an increase of 160 customers sequentially. This was our largest sequential growth in total customer since Q1 2023, reflecting the R&D signs of success from our consumption transformation customers with 100, K plus in IRR grew 17%.

Ron: Sent to 1260 <unk>.

Ron: To account for greater than 85% of our revenue.

Rohan Sivaram: Customers with 1 million plus in ARR grew 24% to 168, reflecting the power of our network effect and customers' continuous standardization on our data streaming platform. NRR was healthy and in line with our target range of 120% to 125% for this year.

Ron: Customers with 1 million plus in R&R grew 24% to 168, reflecting the power of our network effect.

Ron: Customers continued standardization on our data streaming platform.

Ron: <unk> was healthy and in line with our target range of 120% to 125% for this year.

Rohan Sivaram: Gross retention rate remained strong and was above 90%. As discussed last quarter, we expect NRR to exceed our mid-term target threshold of 125% starting fiscal year 25 as we exit the consumption transformation. RPO was $840.2 million, up 13%. Current RPO was estimated to be $570.6 million, up 20%. As discussed in prior quarters, RPO-related metrics are now less relevant, given our greater focus on driving consumption for our cloud business. Starting this quarter, investors can access our RPO metrics in our Supplemental Financials document on our IR website.

Ron: Retention rates remained strong and was above 90%.

Ron: As discussed last quarter, we expect MLR to exceed our midterm target threshold of 125% starting fiscal year 'twenty five as we exit the consumption transformation.

Ron: <unk> was $840 2 million up 13%.

Ron: <unk> was estimated to be $570 6 million up 20 perfect.

Ron: As discussed in prior quarters, our peer related metrics are now less relevant given our greater focus on driving consumption for our cloud business. Starting this quarter investors can access our RPM metrics in our supplemental financials document on our IR website.

Rohan Sivaram: Now, I would like to discuss our long-term opportunity with our Data Streaming Platform, or DSP. We have driven success with our cloud-native streaming product, with Kafka accounting for a substantial majority of our cloud revenue. Over the last few years, we have added Connect, Process, and Govern to complete our multi-product platform. As Shane mentioned, early customer reception of our stream processing product, Flink, has been strong. As our customers start building and ramping their streaming applications, we expect Flink will contribute to revenue meaningfully in 2025. But Confluent isn't just about streaming and stream processing.

Ron: Now I would like to discuss our long term opportunity with our data streaming platform. Our DSP, we have driven success with our cloud native streaming product with Kafka accounting forward the substantial majority of our cloud revenue.

Ron: Over the last few years, we have added connect process and government to complete a multi product platform as Jay mentioned early customer reception of our stream processing product fleet has been strong as our customers start building and ramping that streaming applications.

Ron: Flink will contribute to revenue meaningfully in 2025.

Ron: But confluent isn't just about streaming and stream processing our growth potential with connect and Dublin is often underestimated legacy integration companies have a massive installed base around connectors and this is a significant opportunity for our connect portfolio connect is our first and largest DSP product after screaming and its revenue grew.

Rohan Sivaram: Our growth potential with Connect and Govern is often underestimated. Legacy integration companies have a massive install base around Connectors, and this is a significant opportunity for our Connect portfolio. Connect is our first and largest DSP product after streaming, and its revenue growth trajectory has been robust. For Govern, the increasing complexity around data, security, and regulation, coupled with the rise of Gen AI, is driving the demand for our Governance product.

Ron: Trajectory has been robust for govern the increasing complexity around data security regulation, coupled with the rise of Gen. AI are driving the demand for our governance products. In fact revenue growth for stream governance has been the fastest of any products we have launched the.

Rohan Sivaram: In fact, revenue growth for Stream Governance has been the fastest of any product we have launched to date. The multiproduct aspect of our unified platform adds to our growth vectors and extends our runway to drive durable and efficient growth.

Ron: The multi product aspect of our unified platform adds to our growth vectors and extends our runway to drive durable appreciable growth, let me put it into more context.

Rohan Sivaram: First, each pillar of our platform has the potential to become a large, independent business on its own. The three DSP products, which include Connect, Process, and Govern, are earlier in their S-curve of maturity and adoption than Kafka, but over time, we think their growth potential will be larger than Kafka itself.

Ron: Each printer of our platform has the potential to become a large independent business on its own the three DSP products, which include connect process and govern our earlier in the S curve of maturity and adoption of <unk> Kafka, but over time, we think there's good potential will be larger than Africa itself.

Rohan Sivaram: Second, our opportunity with our DSP products remains in the very early days. In Q1 2024, the three DSP products accounted for approximately 10% of cloud revenue, but with a substantially faster growth rate than our overall cloud business. We expect the three DSP products to remain the fastest-growing part of our business and account for a much larger portion of our cloud revenue over time. And third, multiproduct customers have a higher NRR profile. In Q1 2024, customers using three or more products in our 100K-plus customer cohort increased 47% year-over-year. These multiproduct customers had an NRR substantially higher than the company average.

Ron: Our opportunity with our DSP products remain in very early days in Q1 2020 for the three DSP products accounted for approximately 10% of cloud revenue with a substantially faster growth rate than our overall cloud business.

Ron: The three DSP products to remain the fastest growing part of our business and account for a much larger portion of our cloud revenue overtime and Todd multi product customers have a higher MLR profile in Q1 2020 for customers using three or more products in our 100 gig plus customer cohort increased 47% year over year.

Ron: Multi product customers have an IRR are substantially higher than the company average this underscores the strong network effects of our unified platform, where the success of one product drives additional success can be others.

Rohan Sivaram: This underscores the strong network effects of our unified platform, where the success of one product drives additional success in the other. As our data streaming platform matures and multi-product adoption continues to increase, we believe we will be in a stronger position to address the $60 billion market opportunity ahead. Before turning to our financial outlook, I'd like to note that our guidance philosophy is consistent with prior quarters, with the overall objective of setting prudent and achievable targets.

Ron: Our data streaming platform matures and multi product adoption continues to increase we believe we will be in a stronger position to address our 60 billion market opportunity ahead.

Speaker Change: Before turning to our financial outlook I'd like to note that our guidance philosophy is consistent with prior quarters with the overall objective of setting prudent achievable targets.

Rohan Sivaram: We don't forecast a better or worse macro environment in our guidance. And as a reminder, beginning with the third quarter of 2024, we will fully transition to providing total subscription revenue guidance only. Now, let's turn to guidance.

Ron: We don't forecast, a better or worse macro environment, and our guidance and as a reminder, beginning in the third quarter of 2024, we will fully transitioned to providing total subscription revenue guidance only.

Rohan Sivaram: For the second quarter of 2024, we expect total revenue to be in the range of $229 to $230 million, representing growth of 21% to 22%, and subscription revenue to be in the range of $217 to $218 million, representing growth of 23% to 24%. Cloud revenue to be approximately 116 million, representing growth of approximately 39%. Non-GAAP Operating Margin at approximately negative 1%, representing an improvement of approximately 8 percentage points, and non-GAAP net income per diluted share to be in the range of four cents to five cents.

Ron: Now, let's turn to guidance for the second quarter of 2024, we expect total revenue to be in the range of 202000 $9 million to $230 million representing growth of 21% to 22%.

Ron: Subscription revenue to be in the range of $217 million to $218 million representing growth of 23% to 24%.

Ron: Cloud revenue to be approximately $116 million representing growth of approximately 39%.

Ron: non-GAAP operating margin at approximately negative 1% representing improvement of approximately eight percentage points and non-GAAP net income per diluted share to be in the range of four to five.

Rohan Sivaram: For the full year 2024, we now expect total revenue to be approximately $957 million, representing growth of approximately 23%, and subscription revenue to be approximately $910 million, representing growth of approximately 25%. Non-GAAP operating margin to break even, representing an improvement of approximately 7 percentage points. Pre-cash flow margin to break even, representing an improvement of approximately 16 percentage points. And non-GAAP net income per diluted share to be in the range of $0.19 to $0.20. Finally, we expect net dilution for fiscal year 24 to be approximately 3%, in line with our mid-term target.

Ron: For the full year 2024, we now expect total revenue to be approximately $957 million representing growth of approximately 23% subscription revenue to be approximately $910 million representing growth of approximately 25% non-GAAP operating margin to breakeven representing.

Ron: Approximately seven percentage points free cash flow margin to breakeven representing improvement of approximately 16 percentage points and non-GAAP net income per diluted share to be in the range of 19 to 20.

Ron: Finally, we expect net dilution for fiscal year 'twenty four will be approximately 3% in line with our midterm target. Our long term target is to bring net dilution down to under 2%, which we expect will drive SBC as a percentage of total revenue down to the mid teens over time in closing we're pleased with that.

Rohan Sivaram: Our long-term target is to bring net dilution down to under 2%, which we expect will drive SPC as a percentage of total revenue down to the mid-teens over time. In closing, we're pleased with our strong top-line and bottom-line performance in the first quarter. Our consumption transformation has shown early signs of success. The value proposition of our multi-product platform is resonating with customers. We will stay focused on delivering innovation and value to our customers while continuing to fine-tune our go-to-market effort, which we believe will put us in a stronger position to capture our market opportunity ahead. Now, Jiri and I will take your questions.

Operator: All right. Thanks, Rohan.

Ron: Strong topline and Bottomline performance in the first quarter our consumption transformation has shown early signs of success there.

Ron: The value proposition of our multi product platform is resonating with customers, we will stay focused on delivering innovation and value to our customers, while continuing to fine tune. Our go to market effort, which we believe will put us in a stronger position to capture our market opportunity ahead.

Speaker Change: Gina and I will take your questions.

Operator: To join the Q&A, please raise your hand on Zoom. And today, our first question will come from Sanjit Singh with Morgan Stanley, followed by RBC. Sanjit, please go ahead.

Gina: Alright, Thanks, Ron joined the Q&A. Please raise your hand on zoom.

Ron: And today, our first question will come from Sanjay <unk> with Morgan Stanley followed by RBC. Please go ahead.

Sanjit Kumar Singh: Yeah, thank you for taking the questions and giving us a solid start to the year. Jay, I want to go back to the big macro environment in terms of just the pace of new software development projects. I remember last year that that definitely, you know, slowed down quite a bit. What are you seeing now in terms of just new software development initiatives? And maybe you can sort of tie that into some of the sales transformation efforts that you are undertaking.

Sanjay: Yes, Thank you for taking the question.

Sanjay: So I would start to the year, Jason I'd go back to the big macro environment.

Speaker Change: A jet.

Speaker Change: Right.

Gina: New software development projects.

Speaker Change: Last year that has definitely slowed down quite a bit what are you seeing now in terms of just new software development initiatives and maybe you can sort of tie that into some of the.

Gina: Information efforts that you have.

Gina: With our new organization.

Unknown Attendee: Yeah, I think we've seen overall a stabilization. You know, I would say the focus for a lot of our customers over the last year was, you know, really heavy focus on cost optimization with some amount of new developments, but really only the most necessary things. And I do think that's picked up a little bit. That's probably most pronounced in the digital native segment, where they were probably the hardest hit last year. And, you know, they probably have the biggest bounce back in terms of focus on AI-related initiatives and other developments. So I would say that's positive.

Speaker Change: Yeah, I think we've seen overall is stabilization.

Speaker Change: The focus for a lot of our customers over the last year was.

Speaker Change: Really heavy focus on cost optimization with some amount of new developments, but really only the most necessary things that I do think thats picked up a little bit.

Speaker Change: That's really most pronounced in the digital native segment, where they were probably the hardest hit last year.

Speaker Change: They probably have the biggest bounce back in terms of focus on AI related initiatives and other developments I would say that as positive.

Speaker Change: And then on the.

Speaker Change: Consumption transformation I think.

Unknown Attendee: And then, you know, on the consumption transformation, I think that's gone really well. You know, I do feel like we've seen, you know, we had to execute a really large number of changes in a pretty short period of time. And, you know, I think we really significantly disrupted the set of changes by rolling out a bunch of system changes, you know, they were well adopted by our field team.

Speaker Change: That's gone really well.

Speaker Change: I do feel like we've seen we have to execute really a large number of changes in a pretty short period of time and I think we've really significantly derisked the set of changes by.

Speaker Change: Rolling out a bunch of system changes that were well adopted by our field team.

Unknown Attendee: You know, they've actually proved themselves with customers, and I think that's shown up in the higher rate of new customer acquisition. And I think one of the nice things is, in addition to just getting more customers, we're actually targeting and getting, you know, higher propensity customers. So it's kind of more volume and higher quality. But so yeah, we felt like that was overall a really good result.

Speaker Change: Actually prove themselves out with customers and I think that's shown up in the higher rate of new customer acquisition and I think one of the nice things is in addition to just getting more customers, we're actually targeting and getting higher propensity customers. So its kind of more volume and higher quality, but so yeah, we felt.

Speaker Change: That was overall a really good result.

Sanjit Kumar Singh: That's great to hear. I really appreciate the breakout on some of the new product contribution in Q1 2024. In terms of the monetization strategy across the pillars of DSP, can you sort of outline that for us, and how does Ableflow potentially get monetized?

Speaker Change: That's great to hear I really appreciate the breakout on some of the new product contribution in Q1 2024 and two.

Speaker Change: The modernization strategy across the pillars and DSP.

Speaker Change: Outlined that for us and how does April flow.

Speaker Change: Don't you get monetized.

Unknown Attendee: Yeah, yeah, so each of those represents kind of a distinct monetization opportunity. So the connectors, you know, we charge for each of these connectors, there's a couple pricing levers, but it roughly correlates with how many instances of the connector and the amount of volume of data flowing. For Flink, you know, it's kind of compute hours, very similar to the models you'd see for other processing services like Snowflake. For governance, it's an uplift that comes as kind of a flat fee as you move to our advanced governance package, as well as something that scales up with your usage of the product. And TableFlow is new, so it's just in early access now; we haven't announced any pricing, but it will also have monetization opportunities to come.

Unknown Attendee: Yeah, yeah.

Speaker Change: Yes, yes, so each of those represents kind of a distinct monetization opportunities of the connectors, we charge for each of these connectors.

Speaker Change: There's a couple of pricing levers, but it roughly correlates with how many instances of the connector and the amount of volume of data flowing.

Speaker Change: It's kind of a compute hours very similar to the models you would see for other processing services like Snowflake.

Speaker Change: For governance.

Speaker Change: The uplift.

Speaker Change: That comes as kind of a flat fee as you move to our advanced governance package as well as something that scales up with your usage of the product.

Speaker Change: End table flows new so it's just an early access now we haven't announced any pricing, but that will also add monetization.

Speaker Change: Opportunities to come along with it.

Sanjit Kumar Singh: I appreciate this call again. Thank you.

Speaker Change: I appreciate the color. Thank you.

Operator: All right, thanks, Sanjit. We'll take our next question from Matt Hepper with RBC, followed by Barclays.

Speaker Change: Alright, Thanks, Sanjay we'll take our next question from Matt Hedberg with RBC, followed by Barclays Matt.

Matthew George Hedberg: Hey, thanks, guys. Congratulations on the results. It's really, really nice to see.

Matthew George Hedberg: Hey, Thanks, guys. Congrats on the results really really nice to see maybe as a follow up to <unk> question. You guys have a lot of company specific drivers that are that are certainly seem to be apparent in your numbers I'm sort of curious, though could you help us think about how important improving hyper scaler trends in growth rates that we're seeing and that is also relevant to your success.

Speaker Change: Yes.

Speaker Change: Just trying to get a sense for how much of it is just sort of more of the environment versus a couple of specifics.

Speaker Change: Yes, yes, it's a good question I mean, I don't know that the specific performance of other companies directly drives us, but theres, obviously, some amount of correlation in all spend in the cloud.

Unknown Attendee: Maybe as a follow-up to Sanjit's question, you guys have a lot of company-specific drivers that are certainly seeming to be apparent in your numbers. I'm just sort of curious, though, could you help us think about, you know, how important improving hyperscaler trends and growth rates that we're seeing in that are also relevant to your success? Just trying to get a sense for how much of it is just sort of more of the environment versus confluence-specific.

Speaker Change: If we were breaking out the different things.

Unknown Attendee: Yeah, yeah, it's a good question. I mean, I don't know that the specific performance of other companies directly drives us, but there's obviously some amount of correlation in all spend in the cloud. You know, if we were breaking out the different things, I would say the success of our consumption transformation thus far is an important factor. You know, I think the kind of DSP components that Rohan outlined, our early contributors probably, Connect is the furthest along, followed by Governance, and Flink just went GA. So that, you know, that's just starting to ramp up to revenue contribution. We'll contribute more, you know, coming into the next.

Speaker Change: I would say the success of our consumption transformation. Thus far that's important factor I think the DSP components that Ron outlined early contributors probably connectors the furthest along followed by governance and <unk>.

Speaker Change: Just <unk>.

Speaker Change: That's just starting.

Speaker Change: <unk>.

Speaker Change: Revenue contribution will contribute more coming into next year.

Matthew George Hedberg: If I could just, one quick follow-up, actually, that's a nice tie, you know, it sounds like, Jay, you mentioned 600 prospects have tried Flink. It's great to hear. I mean, we're starting to hear it show up in partner conversations as well. It sounds like a 25-year-old thing. I'm just wondering, you know, Rohan, when you think about it in terms of guidance, are you considering any Flink contributions in the second half of 24?

Speaker Change: If I could just one quick follow up actually has a nice tie it sounds like Jay you mentioned 600 prospects have tried flanked it's great to hear I mean, we're starting to hear it show up in partner conversations as well it sounds like a 25 thing I'm just wondering.

Speaker Change: Volunteers.

Speaker Change: When you think about it in guidance.

Speaker Change: Considering any flint contribution in the second half of 'twenty four.

Rohan Sivaram: Man, thanks for your question. Well, we've said this before, obviously, Flink is a big opportunity for us. And 2024 is all about adoption, and 2025 is all about monetization. So from an overall, what's included in guidance, we're basically assuming that the contribution, the material contribution from Flink will happen in fiscal year 25.

Jay Crabs: Yes, Matt Thanks for your question.

Jay Crabs: We said this before.

Speaker Change: <unk> is a big opportunity for US and 2024 is all about adoption and 2025 is all about monetization. So from an overall what's included in guidance.

Speaker Change: Basically assuming that the contribution material contribution from fleet will happen in fiscal year 'twenty five.

Speaker Change: Got it thanks guys.

Operator: All right. Thanks, Matt. We'll take our next question from Raimo Lenschow of Barclays, followed by William Blair.

Speaker Change: Alright, Thanks, Matt well take our next question from Raimo <unk> with Barclays followed by William Blair.

Raimo Lenschow: Hey, thank you. Thanks for taking my question, and congratulations from me as well. Jay, on the Blink side, now that you have proper early customer conversations, what are you seeing in terms of the adoption curve you see there? And you obviously have seen Kafka before. What are your early customer conversations there, and what does it drive you to think about the addressable market coming out of that one?

Raimo: Hey, Thank you thanks.

Raimo: Thanks for taking my question and congrats from me as well.

Raimo: On the fleet side.

Speaker Change: Now I'll, let you have proper early customer conversations what are you seeing in terms of.

Raimo: The adoption curve do you see Darrin you, obviously saw have seen coffee Cup before.

Raimo: What's the early customer conversations Darin and what does it drive you should think about the addressable market coming out of that one.

Unknown Attendee: Yeah, I would say it's been very positive, you know, there's incredible enthusiasm in our customer base, you know, really, really across the broad set of customers from the kind of digital natives to large enterprises. You know, it's early in the adoption for any of these cloud offerings. Nobody wants to build production workloads against a pre-GA product, so this kind of milestone of going GA is really kind of the starting line, and then it's really about the build of production workloads, and each workload adds a little bit of continuous revenue production, and as those build up within customers, that's where it starts to contribute.

Darin: Yes, I would say it's been very positive.

Darin: Incredible enthusiasm in our customer base.

Darin: Really really across the broad set of customers.

Darin: Digital natives to large enterprises.

Darin: It's early in the adoption for any of these cloud offerings nobody wants to build production workloads against a pre ta products of this kind of milestone is going.

Darin: It really kind of the starting line and then it's really about the build of production workloads and each workload adds a little bit of continuous revenue production and as those buildup within customers, that's where it starts to contribute meaningfully and so.

Unknown Attendee: And so, you know, overall, both the development of that product and the market reception have gone about as well as we could possibly expect as we kind of initiated the development of the Flink offering. Now it's really on us to go execute it as a business and make customers successful with it, which is obviously a very important next step.

Darin: I'd say overall.

Darin: Both the development of that product and the market reception has gone about as well as we could possibly expect as we kind of <unk>.

Darin: <unk> the development of the flank offering now is really on us to go execute it as a business and make customers successful with it which is obviously a very important next step.

Raimo Lenschow: Yeah, and then one follow-up, Rohan, where I get a lot of questions at the moment from the financial communities about RPO, CRPO, maybe it's worth a reminder of why that's kind of you know how that number came together and and how that number needs to be seen in the overall context of results. Thank you.

Darin: And then one follow up Rowland, where I get a lot of the questions at the moment.

Darin: From the financial community is on <unk>, maybe it's worth a reminder of why that is.

Darin: No.

Rowland: That number came together and how that number needs to be seen in the overall context of our results. Thank you.

Rohan Sivaram: Absolutely. Raimo, we called it out last quarter.

Darin: Absolutely.

Rowland: Raimo, we've called it out last quarter, when we think about the consumption transformation one of the important changes that we are driving is making sure we're driving and incentivizing and focusing on consumption and not the commitment from the customer and what that means is <unk> is nothing but the commitment from.

Rohan Sivaram: When we think about the consumption transformation, one of the important changes that we are driving is making sure that we're driving and incentivizing and focusing on consumption and not the commitment from the customer. And what that means is RPO is nothing but the commitment from the customer. And that's not a huge focus for us because what drives Confluent Cloud is the next unit of consumption. And as a result of that, we said that when you think about the forward-looking indicators of our business, consumption revenue and subscription revenue are true indicators of organic growth for us. And that will probably be a more leading indicator than RPO or CRPO.

Rowland: The customer and that's not a huge focus for us because what drives come through in cloud is the next unit of consumption and as a result of that we said that when you think about the forward looking indicators of our business consumption revenue and subscription revenue are true indicators of organic growth for us.

Rowland: And that will be probably a more leading indicator than <unk>.

Raimo Lenschow: Hmm, very clear. Thank you. I appreciate that.

Speaker Change: Very clear thank you I appreciate that.

Operator: Thanks, Raimo. We'll take our next question from Jason Ader, from William Blair, followed by Wells Fargo.

Speaker Change: Thanks, Raimo, we'll take our next question from Jason Ader with William Blair.

Jason Noah Ader: Blair followed by Wells Fargo.

Jason Noah Ader: Yeah, thanks Shane. Good afternoon, guys.

Jason Noah Ader: Yes. Thanks, Shane good afternoon, guys just wanted to ask about Gen AI.

Unknown Attendee: Just wanted to ask about Gen AI. You gave some customer examples where folks are using your technology as part of Gen AI projects. Can you talk a little bit more about the timing of actual impact on revenue and then what specific products are you selling? Is it just the streaming, or is it some of the other elements of the DSP?

Jason Noah Ader: You gave some customer examples.

Jason Noah Ader: Where folks are using your technology as part of Gen AI.

Jason Noah Ader: Projects can you can you talk a little bit more about.

Jason Noah Ader: The timing of actual impact to the revenue and then what specific.

Jason Noah Ader: <unk> are you selling is it just the streaming or is it some of the other.

Jason Noah Ader: Elements of the DSP.

Unknown Attendee: Yeah, so as we described, I would say that's ramping up, like we're seeing customers are adopting this. Usually, digital natives are a little further ahead in their use cases.

Speaker Change: Yeah Yeah.

Jason Noah Ader: So.

Jason Noah Ader: As we described I would say that's ramping now like we're seeing customers that are adopting this usually the digital natives are a little further ahead in their use cases. This is one of the number of use cases for us it's not the only thing happening.

Unknown Attendee: This is one of a number of use cases for us. It's not the only thing happening, but it's an important one and, I think, a strategic one for customers. So yeah, I think that as these initiatives hit production, I think we'll see an increasing ramp of contribution from them heading into next year. And what their customers are using is really the full platform. Our role in this is to be the kind of data supply chain. So that involves our connectors, involves Quora, our Kafka engine, and it will increasingly involve Flink and the integration into the LLMs that we just announced at Kafka Samba Bangalore.

Jason Noah Ader: But it's an important one and I think a strategic one for customers.

Jason Noah Ader: So, yes, I think that as these initiatives hit production I think we'll see an increasing ramp or contribution from them.

Jason Noah Ader: Heading into next year.

Jason Noah Ader: <unk>.

Jason Noah Ader: What their customers are using us really this whole platform like our role in this is to be the kind of supply chain of data. So that involves our connectors involves.

Jason Noah Ader: Our akaka engine.

Jason Noah Ader: It will increasingly involved flink and the integration into the LMS that we just announced.

Jason Noah Ader: It cost us on the Bangalore, and so I think all of those will be driven by these use cases.

Jason Noah Ader: One quick follow-up for Rohan. Rohan, can you talk about hiring right now? You seem to be doing a good job managing expenses. But I assume that, you know, with things stabilizing, you guys are ramping up some of your hiring. And that's one of the reasons why the operating margins are going to be flat this year. But just maybe some thoughts on hiring. Yeah, I mean...

Speaker Change: And then one quick follow up.

Speaker Change: Ron can you talk about hiring right now.

Speaker Change: Seem to be doing a good job managing expenses, but I assume that where things stabilizing you guys are ramping up some of your hiring and I was one of the reasons why.

Ron: Margins are going to be flat this year, but just maybe some some thoughts on the hiring.

Rohan Sivaram: Yeah, I mean, Jason, when we really think about our resource allocation philosophy, it is obviously driving durable and efficient growth. And when I say durable growth, it's essentially extending our runway for growth over a long period of time. And as we think about that, of course, investment and investment in headcount is a key part of that goal. So, for example, in Q1, we had one of our strongest hiring quarters for the go-to-market organization.

Speaker Change: Yes, I mean, Jason when we when we really think about our resource allocation philosophy. It is obviously driving durable and efficient growth and financially durable growth, that's essentially extending our runway to growth over a long period of time and as we think about that.

Speaker Change: Of course like investment and investment in head Count is a key part of that goal. So for example in Q1, we had one of our strongest hiring quarter as far as the go to market organization, which was great and so I think we feel pretty good with respect to where we are.

Rohan Sivaram: And so, yeah, I think we feel pretty good with respect to where we are and how we are thinking about a balanced approach to growth and profitability. On your question about the margins, as you know, over the last, say, 24 odd months, we've improved our efficiency by over 40 percentage points. And heading into this year, we're on track to deliver the seven percentage point improvement, which is going to get us to break even for the full year. And we're on track to get there.

Speaker Change: How we are thinking about a balanced approach on growth and profitability on your question.

Speaker Change: The margins.

Speaker Change: As you know over the last say 24 odd months, we've improved our efficiency by over 40 percentage points.

Speaker Change: And heading into this year, we're on track to deliver the seven percentage point improvement, which is going to get us to breakeven for the full year and we are on track to get there.

Speaker Change: Good luck thanks.

Operator: Thanks, Jason. We'll take our next question from Michael Turrin with Wells Fargo, followed by Misuhu.

Speaker Change: Thanks, Jason we'll take our next question from Michael <unk> with Wells Fargo, followed by Mizuho.

Michael James Turrin: Hey, great. Thanks.

Michael: Hey, great. Thanks, I appreciate you taking the question Jay back to flank is there a way for us to think about the customers. You see is best suited to take advantage of the offering I'm wondering if the addition of platform is important from that perspective, and then any early sense you can provide us around how getting newer products to Jay can help.

Speaker Change: They go to market conversations are shifting more towards consumption profile in a way from bookings.

Unknown Attendee: I appreciate you taking the question. Jay, back to Flink, is there a way for us to think about the customers you see as best suited to take advantage of the offering? I'm wondering if the addition of platform is important from that perspective. And then, any early sense you can provide us around how getting newer products to GA can help as the go-to-market conversations are shifting more towards consumption profiles and away from bookings?

Speaker Change: Yes, yes.

Unknown Attendee: Yeah, yeah, I'm happy to do that. So, you know, we've certainly seen interest across our customer base. One of the things that we will see is a slightly different dynamic between the Confluent platform Flink offering and the cloud offering. With the cloud offering, early versions of the cloud offering tend to be best suited to new use cases, just beginning development, whereas there's more of a lift and shift opportunity on premises, as well as, you know, suiting new use cases.

Jay Crabs: I'm happy to do that so we've certainly seen interest across our customer base. One of the things that we will see is a slightly different dynamic between the console platforms link offering in the cloud offering.

Jay Crabs: The cloud offering the early versions of the cloud offering tend to be best suited to new use cases, just just beginning development, whereas theres more of a lift and shift opportunity on premise as well.

Jay Crabs: Seating new use cases over time as that cloud offering reaches feature complete this proves itself out with customers there will be more of a shift of existing fleet core clubs. That's the behavior, we saw with Kafka, where the early adoption was the incremental use case and the lift and shift just kind of large.

Unknown Attendee: Over time, as that cloud offering reaches future completeness and proves itself out with customers, there will be more of a shift of existing Flink workloads. That's the behavior we saw with Kafka, where early adoption was the incremental use case, and the lift and shift of kind of large install bases took more time. So I think we'll see a similar behavior here, and that's what we've seen with customers.

Jay Crabs: Install basis took more time, so I think we'll see a similar behavior here and that's what we've seen out of customers. Nonetheless across the full set of customers. There is a ton of eagerness. So people are kind of lining up even if theres. Some feature they're waiting on their eagerly awaiting the delivery of that future. So I think that we will see growth on both dimensions in terms of why we.

Unknown Attendee: And nonetheless, across the full set of customers, there's a ton of eagerness. So people are kind of lining up, even if there's some feature they're waiting on, you know, they're eagerly awaiting the delivery of that feature. So, yeah, I think that we'll see growth on both dimensions. In terms of why we added it to the software offering, you know, the Confluent platform, that was by popular demand. You know, originally, the intention was just to do it in the cloud.

Jay Crabs: Additive to the software offering.

Speaker Change: Comparable platform that was by popular demand.

Speaker Change: And the intention was just to do it cloud ultimately we have a set of customers that have pretty extensive on premise operation. Some of them are very big users and they were very eager to abbott operating for them as well.

Unknown Attendee: Ultimately, we have a set of customers that have pretty extensive on-premise operations, some of whom are very big Flink users, and they were very eager to have an offering for them as well. And for us, you know, our goal is to serve customers everywhere. And so as soon as we had capacity to kind of take on the development of that, we added plans for that and built it up.

Speaker Change: Our goal is to serve customers everywhere and so as soon as we add capacity to kind of take on the development of that we added plans for that and build it out.

Michael James Turrin: Rohan, if I may just ask you to comment from your perspective on how the go-to-market changes you've made are progressing and how that impacts your confidence around the initial fiscal year guide you framed alongside Q3. It's encouraging to see the numbers move up, but just any additional context is useful. Thanks.

Speaker Change: Great got it.

Speaker Change: If I may just if you can comment from your perspective on how the go to market changes you've made are progressing and how that impacts.

Speaker Change: Your confidence around the initial fiscal year guide you framed alongside Q3, it's encouraging to see the numbers move up but just any additional context. This useful thanks.

Rohan Sivaram: Absolutely. Well, Jay touched on it. I mean, early indicators from the consumption transformation have been very positive. And we've gone through made a lot of changes with respect to processes, systems, and you know, some of the early data points, for example, if you look at the customer ads that we had in Q1, the highest we've had in five quarters, obviously early, but very positive. And then when you look at our Q1 performance in general, we're very pleased with our total revenue performance and, particularly, our cloud revenue performance and growth we saw 45% year over year.

Speaker Change: Absolutely.

Speaker Change: Touched on it I mean.

Speaker Change: Early indicators from the consumption transformation has been very positive and we've gone through made a lot of changes with respect to processes systems and even some of the early data points. For example, if you look at the customer adds that we had in Q1 the highest we've had in five quarters, obviously early but very positive.

Speaker Change: And then when you look at our Q1 performance in General we're very pleased with our total revenue performance and particularly our cloud our cloud revenue performance.

Rohan Sivaram: And that momentum has actually continued into the first month of the second quarter as well. So when you kind of put this into context, Michael, for the full year, we've increased our full year guidance from 22% to 23%. And what has also happened is we've delivered a strong Q1 and a strong guide for Q2. So that has somehow de-risked the second half of the year in a manner which, you know, I'm candidly very happy about.

Speaker Change: The growth, we saw a 45% year over year.

Speaker Change: Momentum has actually continued into the month one of the second quarter as well. So when you kind of put this into context, Michael for the full year, we've increased our full year guidance from 22% to 23%.

Speaker Change: And what has also happened is we've delivered a strong Q1 with a strong guide for Q2, so that has somehow derisk the second half of the year in a manner, which candidly.

Speaker Change: Candidly very happy about and more importantly, when you look at the growth rates plus comp with the second half that was obviously a point of discussion same time last quarter now we're looking at flattish because of the nature of our first half performance. So overall I would say early indications very positive feel good about our full year guide.

Rohan Sivaram: And more importantly, when you look at the growth rates, first half was the second half, that was obviously a point of discussion at the same time last quarter. Now we're looking at flattish because of the de-risk nature of our first half performance. So overall, I would say the early indication is very positive. I feel good about our four-year guide and, obviously, happy about our Q1 performance.

Michael James Turrin: Very clear. Thank you.

Speaker Change: And obviously happy about our Q1 performance.

Speaker Change: Great. Thank you.

Operator: Thanks, Michael. We'll take our next question from Gregg Moskowitz with Nisuho, followed by Anita. Hey, thank you for taking the questions.

Speaker Change: Thanks, Michael we'll take our next question from Gregg Moskowitz with Mizuho followed by Needham.

Gregg Steven Moskowitz: Jay, obviously, there's a lot of buzz in the industry around Apache Iceberg. So once TableFlow becomes GA, what are your expectations for the adoption curve among your install base? Also, do you think that it will help you land new logos as well?

Gregg Steven Moskowitz: Hey, Thank you for taking the questions Jay obviously, theres a lot of buzz in the industry around Apache iceberg. So once table flow becomes what are your expectations on the adoption curve among your installed base.

Gregg Steven Moskowitz: So do you think that it will help you land new logos as well.

Unknown Attendee: Yeah, yeah, I think it will. You know, we were actually expecting a fair amount of enthusiasm around this. As you said, there's a great deal of buzz around Iceberg. Despite that, I think we were actually surprised by how widespread the interest was. And we felt like, well, in many ways, the analytics environment is kind of, you know, a little bit to the side of the team that we naturally serve. We weren't sure if they would have a direct interest in that.

Jay Crabs: Yeah, Yeah, I think it will.

Jay Crabs: We were actually expecting a fair amount of enthusiasm around this as you said there is a great deal of buzz around iceberg.

Jay Crabs: Despite that I think we were actually surprised by how widespread the interest was and we felt like while in many ways, sometimes the analytics environment is kind of.

Jay Crabs: A little bit to the side of the team that we naturally serve we werent sure. If they would have a direct interest in that but in fact, it's been Ah ha.

Unknown Attendee: But in fact, there's been a huge drop in the topic of discussion in almost every conversation that I've had with customers. So now it's on us to, you know, deliver a GA product. This is just the, you know, first step in that journey.

Jay Crabs: Huge drop and topic of discussion in almost every conversation that I've had with customers. So now it's on us to do.

Jay Crabs: Liver of GAA product. This is just the first step in that journey, so it would be too.

Unknown Attendee: So, you know, it'd be too early to project the rate of adoption or, you know, revenue contribution, whatever. But we feel that this has a ton of potential as it comes out on the market. And as I said, it does kind of align with our business in, I think, a really fantastic way. Confluent is very much about opening up data and sharing it across an organization. And this is a fantastic mechanism for us to do that. In many ways, the fragmentation of the analytics market makes it hard to deliver data in the volume that we would like across all the different systems there.

Jay Crabs: Too early to project the rate of adoption or revenue contribution or wherever but we feel that that has a ton of potential as it comes out onto the market and as I said it it does kind of align with our business in I think a really fantastic way confluence very much about opening up data and sharing it across an organization and this is a fantastic.

Jay Crabs: Mystic mechanism for us to do that in many ways. The fragmentation of the analytics market made it hard to deliver data in the volume that we would like across all the different systems out and this really helps with that and our ability to integrate that directly into Cora and offer that data in a very natural low friction.

Gregg Steven Moskowitz: And this really helps with that. And our ability to integrate that directly into Quora and offer that data in a very natural, low friction, you know, low overhead way, I think, is a great competitive differentiation. And, you know, I think it's a huge boon to that area as well, where one of the challenges in that environment is always getting access to high-quality, reliable data that's up to date. So, yeah, I think we're very excited about it. You know, it's still early, and we have to go, finish the delivery of the product, and make all the customers happy. Okay, very, very helpful. And then I

Jay Crabs: Low overhead way I think is a great competitive differentiation.

Jay Crabs: And I think a huge boon to that area as well, where one of the challenges in that environment sellers getting access to high quality reliable data that subsidy. So so yes, I think we're very excited about it it's still early and you have to go finish finish the delivery of the product and make all the customer success.

Rohan Sivaram: Very, very helpful. And then, either for you or for Rohan, we've spoken before about the potential to do a lot more business with SIs going forward. You know, the new Accelerate with Confluent program, will that or can that be a difference maker in your view? And if so, why?

Speaker Change: Okay very very helpful. And then either for you or for <unk>. So we've spoken before about the potential to do a lot more business with us is coming forward.

Speaker Change: The new accelerate with confluent program.

Speaker Change: Will that or can that be a difference maker in your view and if so why.

Operator: Yeah, Rohan. You want to take that? Well, we'll be happy to. Greg, I mean, we've called it out before as well when we think about the broader partner ecosystem and kind of leveling up a little bit. That's an opportunity, which is in the early innings, most of the opportunities ahead of us. So specifically around SI and the Accelerate program that you called out, absolutely, that's an opportunity for us to drive revenue. But again, it's early days. So it's not something you're going to see next quarter or next month.

Speaker Change: Yeah, Ron do you want to take that we'll be happy to.

Ron: Greg I mean, we've called it out before as well when we think about the broader partner ecosystem and kind of up leveling a little bit better.

Greg: That's an opportunity which is in the early innings most of the opportunities ahead of us so specifically around sorry.

Ron: Accelerate program that you called out absolutely that's an opportunity for us to drive revenue.

Ron: But again, it's early days, so it's not that something youre going to see next quarter or next month. It is a huge opportunity for us and we're working very hard to make sure that we're taking advantage of that opportunity. So long story short I think.

Rohan Sivaram: It is a huge opportunity for us, and we're working very hard to make sure that we're taking advantage of that opportunity. So, long story short, I think SIs, and, in general, GSIs, and the partner ecosystem will continue to be a focus for us as we look ahead.

Ron: And in general of GSI and the partner ecosystem will continue to be a focus for us as we look ahead.

Speaker Change: Thank you.

Operator: Great. We'll take our next question from Mike Cikos with Needham, followed by TD.

Speaker Change: Alright, well take our next question from Mike <unk> with Needham followed by TD Cowen.

Michael Joseph Cikos: Hey, thanks, Shane. And thanks, Jay. Thanks, Rohan.

Mike: Thanks Shane.

Mike: <unk>.

Mike: Thanks, Jay Thanks, Ron I wanted to come back to the multi product adoption that you guys are citing today.

Mike: And what I was thinking through and I just wanted to stress test. This is it fair to think that.

Mike: We're shifting this go to market to prioritize consumption over commitments is actually driving faster adoption across confluence platform or is it or is it still too early to start seeing this in the numbers. This has been a slow go.

Mike: That's something to come as a result of this go to market transformation you guys have done.

Unknown Attendee: I wanted to come back to the multiproduct adoption that you guys are citing today. And what I was thinking through, and I just wanted to stress test this, is it fair to think that your shift in this go-to market to prioritize consumption over commitments is actually driving faster adoption across the Confluence platform? Or is it still too early to start seeing this in the numbers? This has been like a slow go.

Speaker Change: Yes, it's actually it's a very good observation. So this is a subtle point.

Mike: But previously the sales team really sold commitments, which was just dollars and so the incentive to drive adoption of these DSP components was much less right of course, if the customer sprint will consume more as it comes time for them to renew next year, they might commit tomorrow, but that payoff could be.

Unknown Attendee: But that's something to come as a result of this go-to-market transformation you guys have put in place. Yeah, it's actually, it's a very good observation. So this is a subtle point.

Unknown Attendee: But previously, the field team really sold commitments, which were just dollars. And so the incentive to drive adoption of these DSP components was much less, right? Of course, if the customer adopts Splink, they'll consume more. As it comes time for them to renew next year, they might commit to more. But that payoff could be, you know, a year out, you know; it's somewhat delayed.

Mike: A year out.

Unknown Attendee: In a consumption world, of course, as soon as the consumption ramps up, the, you know, immediate compensation arrives, right? And so that payoff is much more immediate. And so the consumption transformation was actually quite important for driving the adoption of these additional components around Kafka. In terms of, you know, have we seen that effect? Yeah, I think we've seen an increased focus from our field team on these components. You know, the use cases around that, it's not like it just materializes overnight all in one quarter; that will build.

Mike: It's somewhat delayed in our consumption world of course as soon as the consumption ramps higher.

Mike: The immediate.

Mike: Compensation arrives right and so that payoff is much more immediate and so the consumption transformation was actually quite important for driving adoption of these additional components around kafka.

Mike: In terms of.

Mike: Have we seen that effect I think we have seen an increased focus from our field team on these components.

Unknown Attendee: The use cases around that it's not like it just materialized as overnight all in one quarter that will build.

Unknown Attendee: But, you know, getting that model right to be set up for multiproduct delivery was actually a substantial motivation for us in doing this more quickly, because we felt we had really good offerings now around Kafka, and we wanted to make sure that we were set up to sell them. Awesome.

Mike: Getting that model right to be set up for multi product delivery was actually a substantial motivation for us in doing this more quickly because we felt we had actually very good offerings now around Costco and we wanted to make sure that we were set up to sell them.

Michael Joseph Cikos: And then just to follow up on the go-to-market, a bit of a two-porter here. But I guess to start with, Jay, like, it's interesting, one of the things that I think you guys are calling out is getting your scene from even higher quality customers, despite the fact that you're not pressing on commitments, right? And I would have thought, or the presumption would be, that if you're not pressing on commitments, you might get some lower-quality customers.

Speaker Change: Awesome and then just a follow up on the go to market a bit of a two parter here, but I guess, let's start with Chile. It's interesting one of the things that I think you guys are calling out is attach youre seeing from even a higher quality customers. Despite the fact that youre not pressing on commitments right and I would've thought.

Mike: The presumption would be that if youre not pressing on commitments you might get some lower quality customers. So can you kind of tease that out for folks I think that would be beneficial and then yes, I guess the second piece of roll on if you could just articulate like.

Michael Joseph Cikos: So can you kind of tease that out for folks? I think that would be beneficial. And then, yeah, I guess the second piece for Rohan, if you could just articulate, like, I know there was a lot of angst into the first half of this year given the go-to-market changes, but like, what more is there to do on your front now that you guys are kind of clicking along here with four months and change behind you?

Mike: I know there was a lot of angst into the first half of this year given the go to market changes, but like what more is there to do on your front now that you guys are kind of clicking along here with.

Michael Joseph Cikos: At four months and change behind you.

Unknown Attendee: Yeah, yeah, it's a great question. So I'll start with a bit on customers. Yeah, so the change we made on the field side was to directly incentivize the land, you know, as part of the comp plan. But not only that, but to actually target a set of high potential customers that we felt were particularly important and, you know, compensate even more highly for those because those will be worth a lot more to Confluent as they ramp up to large consumption.

Speaker Change: Yeah, Yeah, it's a great question, so I'll start with a bit on customers.

Speaker Change: So the change we made on the field side was to directly incentivize the land as part of the comp plan, but not only that to actually target a set of high potential customers that we felt were particularly important for band it.

Mike: Compensate even more highly for those because those will be worth a lot March coming from alliance, United as they ramp to large consumption.

Unknown Attendee: And so what was exciting to US was not only did the volume of customers go up but then as you said, yes, those customers were actually better targeted into that set of high propensity spenders than they had been previously and I think that's just the direct result of the incentives and we had that differentiate.

Unknown Attendee: And so, you know, what was exciting to us was not only did the volume of customers go up, but then, as you said, those customers were actually better targeted into that set of high propensity spenders than they had been previously. And, you know, that I think that's just the direct result of the incentives. And, you know, we had that differentiation because, as you said, we wanted to make sure these were high-quality customer additions. And I'll let you take the second half, Rohan.

Rohan Sivaram: Because as you said, we want to make sure. These are high quality customer additions that were picking up and.

Rohan Sivaram: And I'll, let you take the second half run.

Rohan Sivaram: Yeah, Mike, on the second half, we're obviously we saw this was the first quarter of the transformation. And as Jay called out earlier, the early indications have been very positive, which showed up in our cloud performance for the quarter. And more importantly, when we look at our month one, and how we are entering Q2, we feel good that some of the momentum and actually carried on to Q2. So that's good. But in general, like we still have a couple of quarters of execution that we need to focus on. But if you ask me, how am I feeling?

Unknown Attendee: Yes.

Rohan Sivaram: Mike on the second half.

Rohan Sivaram: We're obviously, we saw this with the first quarter of the transformation and as <unk> called out earlier. The early indications have been very positive which showed up in our performance for the quarter and more importantly, when we look at our month, one and how we are entering Q2, we feel good that some of the momentum and actually.

Rohan Sivaram: Added onto Q2, so that's good but in general like we still have a couple of quarters of execution that we need to focus on like if you ask me how am I feeling obviously, what's evident in our Q1 performance and our Q2 guide, which are strong and which we feel are.

Rohan Sivaram: Obviously, this is evident in our Q1 performance and our Q2 guidance, which are strong and which we feel are ahead of our expectations. And what that does is the strength in the first half is also de-risking our second half from an overall guidance perspective. So overall, where we are, we feel really good with the transformation. But at the same time, we still need to execute a couple of more quarters.

Rohan Sivaram: Ahead of our expectations and what that does is the strength in the first half and also derisking our second half from an overall guidance perspective. So overall, where we are we feel really good with the transformation, but at the same time, we still need to execute a couple of more quarters.

Michael Joseph Cikos: Thank you for that.

Speaker Change: Great. Thank you for that.

Operator: Thanks, Mike. We'll take our next question from Derek Wood with T.D. Cowan, followed by Bernstein.

Michael Joseph Cikos: Thanks, Mike We will take our next question from Derrick Wood of TD Cowen followed by Bernstein.

James Derrick Wood: Great. Thanks, guys. It's nice to chat.

Operator: Great.

Unknown Attendee: Guys, nice to chat with you. Jay, you mentioned having gone through some pricing changes recently. Can you remind us what changes you made and what kind of dividends you're expecting to see as this gets absorbed by the market? Yeah, there are a set of changes. Some of these are actually product offerings that effectively allow better TCO and incentivize the use of our multi-tenant offerings, which are more efficient for us. So, we announced freight clusters at Kafka Summit Bangalore. We announced the enterprise cluster type, which is a high-performance multi-tenant offering with private networking.

James Derrick Wood: Thanks, guys nice to chat with you.

Unknown Attendee: Jay you mentioned having.

Unknown Attendee: Gone through some pricing changes recently can you remind us what changes you've made and what kind of dividends you are expecting to see as this gets absorbed in the market. Yes, yes. There is a set of changes some of these are actually product offerings, which effectively allow better tcl and incentivize the use of our multi multi.

Unknown Attendee: Tenant offerings, which are more efficient for us So we announced freight clusters in Congress on the Bangalore, We announced enterprise cluster type.

Unknown Attendee: Which is a high performance multi tenant offering with private networking, we made adjustments to some of the throughput oriented pricing.

Unknown Attendee: We made adjustments to some of the throughput-oriented pricing, so there were a number of changes that came out. All of these were meant to reduce friction in the land and expand process.

Unknown Attendee: So there was a number of changes.

Unknown Attendee: That came out all of these were meant to reduce friction in the land and expand process. We thought about this consumption transformation.

Unknown Attendee: When we thought about this consumption transformation, a big part of it was changes on the field team, changes in our systems, changes in compensation. But I think going along with that, we felt it was very important that there not be a ton of product or pricing friction in that land process. So if we're trying to tell the team to sell in a way that gets customers up and going, it can't be the case to get to a reasonable price if there's a six-month negotiation at the very front door of the process. And so those changes have lined up with that. Why do you do that?

Unknown Attendee: A big part of it was changes on the field team changes in our systems changes in compensation, but I think going along with that we felt it was very important that there not be a ton of product or pricing friction in that land process alright. So if we're if we're trying to tell the team to go sell in a way that gets customers up and going it can't be the key.

Unknown Attendee: <unk> get to a reasonable price, there's a six month negotiation.

Unknown Attendee: The front door of the process and so those changes have lined up with that.

Unknown Attendee: It's ultimately because there's a ton of open-source Kafka, and we want to soak that up with our cloud offering. We feel that it's very important. So kind of growing the breadth of that customer base sets us up for all the growth in those customers over time. And, you know, we do feel like these kinds of changes and new offerings unlock workloads that would have been harder to access. And that comes out of the TCO of the offering, right?

Speaker Change: Why do that.

Unknown Attendee: Simply because there is a ton of open source Kafka and we want to go to soak that up with our cloud offerings. We feel that's very important so kind of growing the breadth of that customer base that sets us up for all the growth in those customers over time, and we do feel like these kind of changes and new offerings unlock workloads.

Unknown Attendee: That would have been harder to access and that comes out of the <unk>. The offering right. We've talked in the past about how Cora is able to really offer a better <unk> for customers and it's important that we make sure we have offerings that cut across all the different workloads. They have so that it is a bit of a no brainer across everything they do not just a certain workload type or a certain use case.

James Derrick Wood: We've talked in the past about how Quora is able to really offer a better TCO for customers. And it's important that we make sure we have offerings that cut across all the different workloads they have so that it's a bit of a no-brainer across everything they do, not just a certain workload type or a certain. So that was our goal. Yeah, that's a helpful color.

James Derrick Wood: So that was our goal.

Speaker Change: Yes, that's helpful.

Speaker Change: Helpful color and I don't know for Jay or Iran. You guys talked about.

Unknown Attendee: And I don't know, Jay or Rohan, you guys talked about the rebound and digital native consumption trends. Wanted to ask about the financial services vertical, which is obviously important for you. Just curious what you're seeing there around demand conditions and deal sizes, and whether you're seeing much composition change in platform versus cloud. Yeah, yeah, that's continued to be a strong segment for us.

Unknown Attendee: Rebound in digital native consumption trends.

Unknown Attendee: Wanted to ask about financial services vertical which is obviously important for you just curious what youre seeing there around demand conditions and deal sizes, and whether youre seeing much composition change in platform versus cloud.

Unknown Attendee: And over the last few years, we have seen a pretty significant ramp-up in Confluent Cloud adoption. And I would say that that happened first in the smaller banks. And then, over time, that spread to some of the largest financial institutions, which tend to be a little bit slower.

Unknown Attendee: Yeah, Yeah. Yeah. That's continued continue to be a strong segment for us and over the last few years, we have seen a pretty significant ramp up in comparable clouded option and I would say that that happened first in the smaller banks and then over time that spread too.

Unknown Attendee: Largest financial institutions and they tend to be a little bit slower to start with the new cloud offering is actually very substantial security reliability.

Unknown Attendee: To start with the new cloud offering, there's actually very substantial security, reliability, and scrutiny that goes into the adoption of any part of their stack. But increasingly, we're really a great fit for their use cases. And they actually allow them to meet the requirements that they have faster than if they were trying to build this out themselves. And so we've started to see great adoption of cloud and financial services. And I think that's a very promising thing, as these very large institutions open up something that is very low friction to consume across their very broad set of use cases. So we're really excited about kind of getting in the front door of a lot of these very large banks.

Unknown Attendee: It goes into the adoption of any part of their stack.

Unknown Attendee: But increasingly we're really a great fit for their use cases and actually allow them to meet the requirements that they have faster than if they were trying to build this out themselves and so we've started to see greater adoption of cloud in financial services, I think thats, a very promising thing.

Unknown Attendee: As these very large institutions open up something that it was very low friction to consume.

Unknown Attendee: Cross Theyre very broad set of use cases, so we're really excited about kind of getting in the front door in a lot of these very large banks.

James Derrick Wood: Great, thanks, and congrats.

Speaker Change: Great. Thanks Congrats.

Operator: Thank you. Our next question will come from Peter Wieck on Bernstein, followed by Guggenheim.

James Derrick Wood: Thank you. Our next question will come from Peter <unk> with Bernstein, followed by Guggenheim.

Peter Wieck: Thank you very much. It's obviously great to see the continued momentum on the cloud side and the, you know, transition to consumption working out kind of as you planned. But, you know, I may have missed it, but I feel like we haven't talked very much more on the platform side, where I think we saw a sequential step down in revenue. And I wonder, you know, what we should think about some of that, you know, a little bit more weakness there, and whether or not some of that's cannibalization of people moving to the cloud.

Operator: Okay.

Peter Wieck: Thank you very much.

Peter Wieck: Yes.

Peter Wieck: Obviously, great to see the continued momentum on the cloud side and the.

Peter Wieck: Transit mission to consumption.

Peter Wieck: Working out kind of as you plan.

Peter Wieck: But.

Peter Wieck: I may have missed it but I feel like we haven't talked very much more on the platform side, where I think we saw a sequential step down.

Peter Wieck: Revenue and and I wonder.

Peter Wieck: How we should think about some of that a little bit more weakness there and.

Peter Wieck: Whether or not some of that's cannibalization of people moving to cloud and so it's just some of the some underlying share shifting or whether or not.

Peter Wieck: And so it's just some of the underlying share shifting, or whether or not we should think about, you know, like, slower growth going forward on that side of the business, given that it's an important part of the revenue stream. Yeah, you want to speak to that, Rohan?

Rohan Sivaram: We should think about.

Peter Wieck: Like.

Rohan Sivaram: Slower growth going forward on that side of the business given that it's an important part of the revenue stream.

Rohan Sivaram: Yeah, you want to speak to him about that, Rohan? Yeah, I'll be happy to take it.

Rohan Sivaram: Yes speak to that Ron.

Rohan Sivaram: Thanks for your question, Peter. Well, when we look at our Confluent platform performance, we're very pleased. In fact, we grew 15% year over year. And when you generally think about the platform business, more of a reminder, what happens is about 20% of total contract value is recognized as licensed revenue upfront. So what that can do, that can add a little bit of lumpiness in the revenue, purely based on the timing of large deals or the timing of renewals for large deals. Those have an impact.

Rohan Sivaram: Be happy to take it.

Speaker Change: Thanks for your question Peter.

Rohan Sivaram: When we look at our confluent platform performance.

Rohan Sivaram: We're very pleased actually we grew 15% year over year and when do you generally think about the platform business model as a reminder.

Rohan Sivaram: What happens is about 20% of total contract value is recognized as license revenue upfront. So what that can do that can add a little bit of lumpiness in the revenue purely based on the timing of large deals or the timing of renewals for large deals those have an impact.

Rohan Sivaram: But when I take a step back, and I look at, say, the last 12 months for this business, we've been very pleased with the overall momentum. And Jay also mentioned with respect to product innovation. We launched Flink on prem, which is obviously going to help this part of the business as well. So yeah, I mean, you know, listen. We've said that Confluent needs to be wherever our data and applications reside.

Rohan Sivaram: When I take a step back and I look at say the last 12 months for this business.

Rohan Sivaram: We've been very pleased with the overall momentum and gene also called out with respect to product innovation.

Rohan Sivaram: Launched.

Rohan Sivaram: On Prem, which are obviously going to help as part of the business as well.

Rohan Sivaram: I mean listen we've said that.

Rohan Sivaram: <unk> needs to be wherever our data and applications are site. If it's on Prem we need to be on Prem if it's in the cloud we need to be cloud just keeping that in mind. We don't feel that this is going to be an important part of the business as we look ahead.

Rohan Sivaram: If it's on premises, we need to be on premises. If it's in the cloud, we need to be in the cloud. Just keeping that in mind, you know, we do feel that this is going to be an important part of the business as we look ahead.

Speaker Change: Thank you.

Rohan Sivaram: Alright, let's take our next question from Howard <unk> with Guggenheim followed by J P. Morgan.

Peter Wieck: Great. Thanks for taking the question.

Speaker Change: Great. Thanks for taking my question Jay can you talk about some of the alternative options that you are aware of.

Peter Wieck: The transport layer and Reg architectures, I don't believe that the standard yet.

Speaker Change: And on that point do you have plans to establish a more formalized reference architecture program for.

Peter Wieck: Implementations and perhaps broader influence these cases to really aimed at making affluence the standard for transport and transformation as well yeah. Yeah. There has been a focus for us kind of evangelize in this architecture because as you say it is somebody who's just coming into kind of formation now.

Unknown Attendee: as well. Yeah, yeah, you know, it has been a focus for us to kind of evangelize this architecture, because, as you say, it is something that's just coming into kind of formation now. You know, the reality is, I don't think that there are great alternatives for real-time data movement right outside of Confluent. I would say we have a strong status as a de facto for real-time data movement across the enterprise.

Unknown Attendee: The reality is I don't think that there are great alternatives for our real time data movement right outside of Confluent I would say, we have a strong status as a de facto for real time movement of data across the enterprise there is opportunities for customers to just try and build it in batch theres plenty of batch ETF products.

Unknown Attendee: There are opportunities for customers to just try and build it in batch. You know, there are plenty of batch ETL products. But the reality is that for a lot of these use cases, they're answering questions about the business. And that's really just not good enough.

Unknown Attendee: The reality is though for a lot of these use cases.

Unknown Attendee: They are answering questions about the business and that's really just not good enough.

Unknown Attendee: For a lot of these use cases, its something thats customer support related or in other words youre driving some aspect of the business, we're kind of answering without of data information is very likely to be wrong relative to what the customer was stealing.

Unknown Attendee: You know, for a lot of these use cases, it's something that's, you know, customer support related, or in other words, you're driving some aspect of the business where answering with out of date information is very likely to be wrong relative to what the customer was just doing. And so we are seeing a real push toward real time. And yeah, it's on us to make sure that as that stack solidifies, we have, you know, a permanent position on that.

Unknown Attendee: And so we are seeing.

Unknown Attendee: We'll push towards real time.

Unknown Attendee: Yes, it's on us to make sure that that as that stack solidifies, we have a permanent position in that.

Unknown Attendee: That's great. And maybe I can slip in one more just on the topic of open source Kafka conversions. Can you talk about any progress that you're seeing with the Confluent Migration Accelerator tool, I believe it's called? And is that increasing your wallet share among Fortune 500s? And to what extent are partners using it? Yeah, we're just ramping up.

Speaker Change: That's great and then maybe even slip in one more just on the topic of the open source catheter conversions can you talk about any progress that you're seeing with the <unk> migrated.

Unknown Attendee: This accelerated tool I believe its called <unk>.

Unknown Attendee: Increasing your wallet share among fortune 500, and to what extent are reducing that tool. Yes, we're just ramping that up so.

Unknown Attendee: Not surprisingly, we havent had really a focused effort on these migrations, it's been somewhat more one off customer by customer and so both in terms of tooling and.

Unknown Attendee: Yeah, we're just ramping that up. So, you know, somewhat surprisingly, we haven't really had a focused effort on these migrations. It's been, you know, somewhat more one-off customer by customer. And so both in terms of tooling and, you know, with our partners, creating a focused effort to move customers over. As you can imagine, in any of these situations where there's kind of a better TCO alternative but some effort that's required to make the switch, you want to reduce as much as possible that effort and make it really easy for customers to go from Point A to Point B. So I think it's just coming into being now, you know; we believe that'll contribute over time.

Unknown Attendee: With our partners.

Unknown Attendee: Creating a focused effort to move customers over as you can imagine in any of these situations, where there's kind of a better tcl alternative but some effort that's required to make the switch you want to reduce as much as possible that effort and make it really easy for customers to get from point.

Unknown Attendee: Eight to point B.

Unknown Attendee: So I think thats, just coming into being now we believe that all contribute over the next years.

Speaker Change: Great. Thanks, so much.

Operator: Thank you. We'll take our next question from Pinjalim Bora, with J.P. Morgan.

Speaker Change: Thank you we'll take our next question from pendulum <unk> with J P. Morgan.

Pinjalim Bora: Pinjalim. Hey, thanks for screening me and congrats to everyone for the quarter.

Pinjalim Bora: Hey, Thanks for squeezing me in congrats.

Pinjalim Bora: For the quarter up one one clarification.

Rohan Sivaram: One, one clarification. Help me understand how broad-based the cloud consumption ramp was? I heard it was driven by a select set of customers, so I wanted to clarify. And any way to understand if some of the new AI vendors that you recently added materially contributed in the quarter?

Rohan Sivaram: Help me understand how broad based was the trough consumption than to ramp I heard it was driven by a select set of customers so on to clarify.

Rohan Sivaram: I think we don't understand if some of the new vendors that you recently added materially.

Rohan Sivaram: <unk> contributed in the quarter.

Speaker Change: Yes, I'll take it Ron.

Speaker Change: Happy to paper and Jim Thanks for your question so.

Rohan Sivaram: Yeah, you want to take it, Rohan? Yeah, happy to. Hey, Pinjalim, thanks for your question. So, you know, when you look at cloud performance, I'd put it in maybe two categories: performance and cost, if I had to call it out for Q1. The first one is, when you look at our broad base of customers, we did see stabilization in consumption and net new use cases, and the digital native segment is included in there. So that's good.

Rohan Sivaram: When you look at our cloud performance I'd put it in maybe two categories.

Rohan Sivaram: Performance, if I had to call out for Q1. The first one is when you look at on a broad base of customers. We did see stabilization in consumption and the net new use cases and the digital native segment is inclusive in there. So that's good that's a broad base of our customer and the second call out was.

Rohan Sivaram: That's a broad base of our customers, and the second call out was some of our newer customers. We've seen the ramp up of these newer customers, and I'd say something that we are very pleased about. And the Gen AI customer that you spoke about is probably in that board of customers. It's a few of them that we've run and where the RAM schedule looks in line, and we're pretty happy with that. And that's for Q1. And as we enter Q2, most of these trends have continued into month one of Q2, which has informed our guidance for Q2 as well. So that's the overall context around consumption.

Rohan Sivaram: Some of our newer customers we've seen the ramp up of these newer customers I'd say something that we are very pleased John and the <unk> customer that he spoke about is probably in that cohort of customers. It's a few of them who've kind of rebrand and where the ramp schedule looks in line and we are pretty happy with that and thus far in Q1 and <unk>.

Rohan Sivaram: We entered Q2.

Rohan Sivaram: Most of these trends have continued into month, one of Q2, which has informed our guidance for Q2 as well. So that's the overall context around the consumption patterns.

Pinjalim Bora: Thank you for that. I have one question for you, Jay. We have been picking up on this notion that Slynk SQL, being SQL, which is understood by almost every developer, kind of opens up the aperture versus a skill set of Java developers or, you know, some other thing in bringing in more developers to do more Slink. And then Slink additionally drives more Kafka, that kind of creates a little bit of a flywheel.

Speaker Change: Yes. Thank you for that one question for you Jay.

Pinjalim Bora: Have been picking up on this notion that shrink think sequel being sequel, which is most of them. Mr. Bell almost every developer.

Pinjalim Bora: Opens up the approach or versus a skill set of <unk>.

Pinjalim Bora: Some something else is it bringing in more developers to do most link and then slink. Additionally drives more kafka.

Pinjalim Bora: Creates a little bit of a flywheel are you starting to see some I like this question I mean this question it sounds like my answer already.

Unknown Attendee: Are you starting to see some? I like this question. I mean, this question sounds like my answer already. Go ahead.

Speaker Change: Got it got it.

Pinjalim Bora: No, no, no, Keith Hunter. Are we starting to see that?

Speaker Change: No no no.

Unknown Attendee: Are we starting to see that? Yeah, we are.

Speaker Change: Or are we starting to see that yes, we are.

Unknown Attendee: Yes.

Speaker Change: Our goal is to open up the full set of API. So the first thing we launched with sequel, our intention is to bring out Java on API as well.

Unknown Attendee: We think they serve different use cases that there is a set of kind of core applications that will probably always be in these.

Unknown Attendee: More application oriented programming languages like Java, Theres, a set of more dynamic use cases, and transformations, which are well suited to sequel, one of the powerful things about link is kind of opening up that broad set of tools all on top of our core engine I think that's one of the things Thats made it a leader in the stream processing.

Unknown Attendee: Yeah, our goal is to open up the full set of APIs, so the first thing we launched was SQL. Our intention is to bring out, you know, Java and Python APIs as well. We think they serve different use cases that, you know, there's a set of kind of core applications that will probably always be in these, you know, more application-oriented programming languages like Java, and there's a set of more dynamic use cases and transformations, which are well suited to SQL.

Unknown Attendee: And as we do that yeah. Our goal is very much to make this easier and easier to use.

Unknown Attendee: <unk>.

Unknown Attendee: For a long time I think it's been the case that customers would prefer real time data they would rather work with opposite updated in real time that reacted in real time, they would rather be able to connect things in real time, nobody wants the data to be slow it's actually just been difficult to do that so making this really easy as kind of a core way of.

Unknown Attendee: One of the powerful things about Flink is kind of opening up that broad set of tools, all on top of a core engine. You know, I think that's one of the things that's made it the leader in stream processing. And, you know, as we do that, yeah, our goal is very much to make this easier and easier to use. For a long time, I think it's been the case that customers would prefer real-time data, they would rather work with apps that update in real time, that react in real time, they would rather be able to connect things in real time. Nobody wants the data to be slow.

Unknown Attendee: Willingness like there is an obvious benefit if you can make it not more costly and not more complicated for customers. So when you see us kind of focusing on both this ease of development and Tcl oriented things that really is the kind of core thing that drives us as we do that we think there is a huge opportunity for this whole set of batch data.

Unknown Attendee: It's actually just been difficult to do that, so making this really easy is kind of a core way of enabling this. There's an obvious benefit if you can make it, you know, not more costly and not more complicated for customers. So when you see us kind of focusing on both this ease of development and TCO-oriented things, that really is the kind of core thing that drives us. And as we do that, we think there's a huge opportunity for this whole set of batch data movement batch processing that really needs to move and will move, you know, as the alternative becomes appealing because of that ease of use and TCO.

Unknown Attendee: Move managed batch processing that really needs to move and we will move as the alternative becomes appealing because of that ease of use and tcl.

Speaker Change: Got it thank you.

Operator: All right, thanks. So as a reminder, the Confluent earnings report is now on our website. The report contains our earnings infographic, our one-pagers on our technology, the prepared remarks, and earnings slides from today's call. We encourage you to go take a look. And today, our final question will come from Miller Jump with Shure Securities.

Speaker Change: Alright. Thanks, So as a reminder, the Thompson earnings report, it's now on Ohio website there'll be four contains our earnings infographic on one pagers on our technology. The prepared remarks earnings slides from today's call. We encourage you to go take a look and today. Our final question will come from Miller jump with <unk> Securities.

Miller Jump: Right, great. Thank you for taking the time to answer the question. And I will echo my congratulations on the strong start. So, um, you just talked about the strength in governance. And I'm just curious, like, is the need to get your data estate ready for AI driving more conversations there? And then maybe if you could just remind us what that opportunity looks like, maybe at a unit economics level, if you're spending a dollar on streaming, you know, what does that look like for governance?

Miller Jump: Right great. Thank you for taking the question and I will Echo my congrats on the strong start so.

Miller Jump: Just you talked about the strength in governance and.

Speaker Change: I'm just curious like is the need to get your data estate ready for AI driving more conversations there and then maybe if you could just remind us what that opportunity looks like maybe on a unit economics level. Like you are spending one dollar on streaming what does that look like for governance, yeah. Yeah. It's a great question. So yeah.

Unknown Attendee: Yeah, yeah, it's a great question. So, yeah, AI is definitely one of the drivers. I would say that there is a whole set of forces that have driven interest in data governance. You know, one of those is just the kind of rising compliance regime around data. You know, GDPR is just the start, but there's a long list of things that organizations have to do. The second is around just the safety of data. The third is actually around opening it up.

Unknown Attendee: AI is definitely one of the drivers I would say that theres a whole set of forces that have driven interest in data governance.

Unknown Attendee: One of those is just that kind of a rising compliance regime around data GDP Ars to start, but there's a long list of things that organizations have to do the second is around just the safety of data. The third is actually around opening it up those first two are maybe things you have to do but in order to really take advantage.

Unknown Attendee: Those first two are maybe things you have to do, but in order to really take advantage of data, it has to be the case that the right team can find the right data set, and know what it means at the right time. That kind of discovery process, and documentation is actually really critical to the integrity of data as something that customers can build around and against. And then, as you said, all of that, I think, has been supercharged by AI, where you have a set of applications that are much more data-rich, you know, draw on many more data sources across an organization than a traditional enterprise app. But in order for that to work well, you have to know what's going on where, and is it up to date? Is it getting there in the right way? Is it supposed to be there at all?

Unknown Attendee: That data has to be the case with the right team can find the right data set and what it means at the right time that kind of discovery process documentation is actually really critical to the integrity of data is something that customers can build around and against <unk>.

Unknown Attendee: And then as you say.

Unknown Attendee: All of that I think has been supercharged by AI, where you have a set of applications that are much more data rich you to draw on many more data sources across an organization than a traditional enterprise at night.

Unknown Attendee: And, you know, managing all of that has just gotten harder and harder. And managing it on top of some crusty set of old bespoke pipelines is trending towards impossible. And I think that's one of the things that has driven the rise of data streaming. And the nice thing for us is the ability to bring these governance capabilities right into the platform. So there's not extra effort to go and adopt this, you know, use case by use case, you know, the data is naturally tracked as it flows, you have the lineage of what goes where, and you have kind of strong schemas that allow the creation of these data products that are shared across an organization.

Unknown Attendee: But in order for that to work well you have to know what's going well and is it up to date as youre getting are in the right way as it's supposed to be there at all and managing all of that has just gotten harder and harder and managing it on top of.

Unknown Attendee: Some crusty set of all be spoke pipelines.

Unknown Attendee: Is trending towards impossible and I think that's one of the things that has driven the rise of data streaming and the nice thing for US is the ability to bring these governance capabilities kind of right there with the platform. So theres not extra effort to go and adopt this.

Unknown Attendee: And, you know, this is a really powerful thing for customers as they think about how they use this technology in the large and how they really take advantage of the data they have to better serve customers and be more. And on the unit economics, yeah, that, you know, this will change over time, as that product line develops. The, you know, right now, it is, you know, kind of a step up with some additional usage, as you use And I think that will increase monetization over time. I think it's too early to call the, you know, kind of final ending state ratio for any of these offerings. But we do think that that will be a sizable business for us.

Unknown Attendee: Use case by use case the data is naturally tracks as it flows that you have the lineage of what goes where you have kind of strong schemas that allow the creation of these data products that are shared across the organization and you know this is a really powerful thing for our customers as they think about how they use this technology in the large and how they really take.

Unknown Attendee: Advantage of the day to day, App to better serve customers and be more efficient.

Unknown Attendee: And on the unit economics, Yes, this will change.

Unknown Attendee: Change over time as that product line develops.

Unknown Attendee: Right now it is.

Unknown Attendee: Kind of a step up with some additional usage as you use it more broadly.

Unknown Attendee: I think we are adding more and more functionality around the encryption of fields of data.

Unknown Attendee: Round other aspects of how you use and analyze data and I think that will increase the monetization over time I think it's too early to call the kind.

Unknown Attendee: Final ending state ratio probably for any of these offerings, but we do think that that will be a sizable business for us.

Miller Jump: That is helpful. Thank you. And if I could squeeze in one quick one for Rohan,

Rohan Sivaram: Any gross margin changes to consider as these use cases outside of streaming start to scale?

Speaker Change: That is helpful. Thank you and if I could squeeze in one quick one for <unk> any gross margin changes to consider as these use cases outside of streaming start to scale.

Rohan Sivaram: Yeah, from a gross margin perspective, what we said to Miller is that our long-term target is 75 plus percent gross margin, and we are operating well above that. And it's been consistently above that. So as we look ahead for, say, the rest of the year, we expect to be in the zip code of gross margins. So not a whole lot to call out there with respect to any impact one way or the other on gross margin.

Rohan Sivaram: Yeah from a gross margin perspective, what we've said.

Rohan Sivaram: <unk>, we are essentially our long term targeted 75 plus percent gross margin, we are operating well above that.

Rohan Sivaram: And it's been consistently above that so as we look ahead for CA rest of the year, we expect to be in the ZIP code of gross margins. So not a whole lot to call out there with respect to any impact one way or the other on gross margins.

Operator: All right, thanks for all the questions. This concludes our earnings call today. Thanks again for joining us. Bye, everyone. Thanks, everyone.

Speaker Change: Alright, Thanks for all the questions. This concludes our earnings call today, Thanks, again for joining us by everyone.

Operator: Everyone. Thank you.

Operator: Yes.

Operator: Yeah.

Operator: Yes.

Operator: Yes.

Speaker Change: Thank you.

Operator: Okay.