Q2 2025 Confluent Inc Earnings Call

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Jay Kreps: Fleet load we've seen in the same period of prior years. Rohan will provide further details in his remarks. Encouragingly, we've seen some customers commit to larger multi-year deals following the optimization efforts they undertook last year. This helped accelerate our RPO growth to 31% in the quarter, reflecting the deepening of our customer relationships as they plan for long-term growth. To accelerate use case expansions and support the long-term growth trajectory of our cloud business, we're driving operational enhancements across several areas in the business. This includes two key focus areas Ryan McMahon has identified following his first 90 days as Chief Revenue Officer. First, we're improving coverage ratios between AEs, SEs, and post-sales roles to strengthen execution in the field. This higher-touch integrated approach enhances account ownership and provides tighter customer alignment in driving use cases into production across our enterprise customer base.

Prior years, Ron will provide further details in his remarks encouragingly, we've seen some customers commit to larger multi year deals. Following the optimization efforts Andrea took last year. This helped accelerate our <unk> growth to 31% in the quarter, reflecting the deepening of our customer relationships as they plan for long term growth too.

To accelerate use case expansion and support the long term growth trajectory of our cloud business, we're driving operational enhancements across several areas in the business.

This includes two key focus areas Ryan Mcmahon has identified following his first 90 days as Chief revenue Officer.

First we're improving coverage ratios between Aes <unk> and post sales roles to strengthen execution in the field. This higher touch integrated approach enhances account ownership and provides tighter customer alignment and driving use cases into production across our enterprise customer base. This has shown early results in the second quarter as we have seen a sequential increase of more than 40% in late.

Jay Kreps: This has shown early results in the second quarter, as we've seen a sequential increase of more than 40% in late-stage pipeline progression. Second, we're accelerating the build-out of our DSP specialist team to drive multi-product selling. This team focuses on building repeatable high-impact sales plays that include pricing strategy, go-to-market messaging, and streamlined migration offerings that combine tooling and professional services. We've also seen early signals of success with this specialization model, with several customers accelerating their production go-live of DSP use cases in the quarter. Together, these changes are designed to enable the field to move faster and unlock greater value from our platform selling strategy. In parallel, we're doubling down on three areas where we're already seeing strong traction. The first is replacing CSP streaming offerings with Confluent. We've had success displacing these CSP offerings with win rates well above 90%.

Stage pipeline progression.

Second we are accelerating the build out of our DSP specialist team to drive multi product selling this team focuses on building repeatable high impact sales place that include pricing strategy go to market messaging and streamlined migration offerings that combine tooling and professional services.

We are also seeing early signals of success with the specialization model with several customers accelerating their production go live of DSP use cases in the quarter. Together. These changes are designed to enable the field to move faster and unlock greater value from our platform selling strategy.

In parallel we are doubling down on three areas, where we're already seeing strong traction.

The first is replacing CSP streaming offerings with comfort we have had success displacing the CSP offerings with win rates well above 90%. This is an area, where we feel our product capabilities and Tcs story has improved enormously over the last year with differentiated offerings like break clusters enterprise clusters and work stream.

Jay Kreps: This is an area where we feel our product capabilities and TCO story have improved enormously over the last year, with differentiated offerings like break clusters, enterprise clusters, and warp stream. Already in Q2, we saw more than two dozen displacements against a single CSP offering. We plan to amplify this success by intentionally targeting these offerings and increasing our number of at-bats against these competitors. Speaking of warp stream, we're seeing positive trends there as well. The large majority of our warp stream business in Q2 is incremental. Even in existing customers, we're seeing customers increase their spend with Confluent through warp stream while actually lowering their overall cloud infrastructure costs. For example, two customers, a major retail investing platform and a leading prepaid mobile provider, both deployed warp stream for their high-volume logging and telemetry workloads in Q2.

Already in Q2, we saw more than two dozen displacements against a single CSP offerings. We plan to amplify this success by intentionally targeting these offerings and increasing our number of add backs against these competitors.

Speaking of work stream, we're seeing positive trends there as well the large majority of our work stream business in Q2 as incremental even in existing customers. We're seeing customers increase their spend with confluent through work stream, while actually lowering their overall cloud infrastructure costs for example to customers a major retail investing platform and our leading prepaid mobile provider both deployed.

Work stream for their high volume logging and telemetry workloads in Q2.

Jay Kreps: These customers increased their spend with Confluent by 30% while decreasing overall CSP infrastructure costs roughly 50%. It's a great example of how we're helping customers scale efficiently while delivering meaningful cost savings. The second area that we're doubling down on is our partner ecosystem. Partners are instrumental in broadening our footprint and driving customer expansion, especially as we scale into a multi-product platform company. We continue to see incredible traction in this area. In the past year alone, we've launched a new OEM program and partnered with leading AI vendors to launch a new AI accelerator program. At the same time, we've deepened key partnerships with Jio, SCCC, Databricks, EY, and most recently, Infosys. This expanded collaboration with Infosys, a global leader in next-generation digital services and consulting, is the first major partnership under this new investment.

These customers increased their spend with confluent by 30%, while decreasing overall CSP infrastructure costs, roughly 50% is a great example of how we are helping customers scale efficiently, while delivering meaningful cost savings.

The second area that we're doubling down on is our partner ecosystem partners are instrumental in broadening our footprint and driving customer expansion, especially as we scale into a multi product platform company. We continue to see incredible traction in this area in the past year alone. We've launched a new OEM program and partnered with leading AI vendors to launch a new AI accelerator program.

At the same time, we've deepened key partnerships with Geo as Triple C data bricks UI and most recently emphasis.

This expanded collaboration with emphasis a global leader in next generation digital services and consulting is the first major partnership under this new investment as a partner in our OEM program Infosys has seen firsthand the growing demand for data stream. This is a meaningful step forward in our broader strategy to deepen partnerships with leading system integrators to <unk>.

Jay Kreps: As a partner in our OEM program, Infosys has seen firsthand the growing demand for data streaming. This is a meaningful step forward in our broader strategy to deepen partnerships with leading system integrators. To underscore the strategic value of our partner ecosystem, well over 20% of our business over the past year has been partner-sourced. Looking ahead, our partner ecosystem will be an important area of continued investment and co-innovation. We believe deepening partner engagement across Confluent Platform and Confluent Cloud will fuel our growth and accelerate our global market penetration. The value of our partner ecosystem can best be understood through our customers' lens. A leading global financial market infrastructure provider that processes trillions of dollars of security transactions daily set out to create a shared Kafka service across its business.

Underscoring the strategic value of our partner ecosystem, well over 20% of our business over the past year has been partner sourced looking ahead, our partner ecosystem will be an important areas continued investment and co innovation, we believe deepening partner engagement across confluent platform and confluent cloud will fuel our growth and accelerate our global market penetration the value of.

Our partner ecosystem can best be understood to our customers' lens.

Leading global financial market infrastructure provider that processes trillions of dollars of security transactions daily set out to create a shared kafka service across its business. The goal is to enable real time data streaming at scale with kind of governance needed for a systemically important institution. However, they faced challenges with the specialized staffing required and the complexities.

Jay Kreps: The goal was to enable real-time data streaming at scale with the kind of governance needed for a systemically important institution. However, they faced challenges with the specialized staffing required and the complexities of operating Kafka as a shared enterprise service. As the organization's long-time transformation partner, EY went beyond pure technical guidance. They helped define a broader vision, positioning Confluent as the strategic foundation for enterprise-wide data streaming. After the deal closed, EY and Confluent partnered to launch a modern streaming center of excellence that helped the company evolve from siloed messaging to a unified enterprise-wide streaming strategy. With EY's trusted relationships, the focus has shifted to scaling high-impact streaming use cases across the business. Together, EY and Confluent are building a foundation for sustained innovation, enabling this market leader to turn real-time data into a true competitive advantage. The third area where we're doubling down is Flink.

Operating Kafka is a shared enterprise service.

As the organizations longtime transformation partner UI went beyond pure technical guidance that helps define our broader patient positioning and confluent as the strategic foundation for enterprise wide data streaming.

After the deal closed wind confluent partner to launch a modern streaming center of excellence that helped the company evolve from Siloed messaging to a unified enterprise wide streaming strategy.

With <unk> trusted relationships that focus has shifted to scaling high impact streaming use cases across the business together <unk> and confluence are building a foundation for sustained innovation, enabling this market leader to turn real time data into a true competitive advantage.

The third area, where we're doubling down disciplined while flink is still a small part of our overall business. It has experienced exponential growth with the sequential dollar increase in <unk> are accelerating for four consecutive quarters. Our <unk> business is approaching $10 million in IRR and nearly tripled over the first half of the year. This includes strong contributions from both confluent cloud.

Jay Kreps: While Flink is still a small part of our overall business, it has experienced exponential growth with the sequential dollar increase in ARR accelerating for four consecutive quarters. Our Flink business is approaching 10 million in ARR and nearly tripled over the first half of the year. This includes strong contributions from both Confluent Cloud and Confluent Platform, with a fairly even ARR split between the two. We now have three customers with more than 1 million in Flink ARR and a diverse, rapidly expanding base of customers well into their first set of use cases. Capturing the processing of real-time data is one of the most strategic elements of our DSP strategy. This allows us to make real-time use cases much easier to build and to capture the spend on these use cases. The rapid growth of our Flink offering is evidence that this strategy is working.

<unk> platform with a fairly even split between the two we now have three customers with more than $1 million in <unk> and a diverse rapidly expanding base of customers willing to their first set of use cases.

Sharing the processing of real time data is one of the most strategic elements of our DSP strategy. This allows us to make real time use cases, much easier to build and to capture the spend on these use cases, the rapid growth of our fleet offering as evidenced that this strategy is working.

Jay Kreps: Wix is a great example of the power of our Flink offering. Wix is the global platform behind more than 100 million websites, serving a billion users every year. As they expanded to analytics and AI-driven personalization, it became clear that they needed a more scalable real-time data infrastructure. Their batch pipelines and self-managed Kafka setup simply couldn't keep up. To support their next stage of growth, Wix turned to Confluent Cloud and our fully managed Flink offering. Today, they process over 30 billion events per day in real time across multiple regions and clouds. Flink is now central to Wix's data architecture. It filters, enriches, and joins data streams in real time, powering hyper-personalized web experiences, live A/B testing, and Wix analytics, which gives users and developers immediate insight into site activity. With Flink and Confluent's governance tools, Wix delivers low-latency, trustworthy data at global scale.

<unk> is a great example of the power of our flank offering.

As the global platform behind more than 100 million websites, serving 1 billion users every year as they expand into analytics and AI driven personalization it became clear that they needed a more scalable real time data infrastructure their batch pipelines and self managed kafka setup simply couldnt keep up to support their next stage of growth, which turned to <unk>.

Cloud and our fully managed blink offering today they process over 30 billion events per day in real time across multiple regions and clouds. Blink is now central to Wix as data architecture. It filters enriches and joins data streams and real time powering hyper personalized web experiences live AB testing and Wix analytics, which gives users and developers immediate.

Site <unk> activity.

With Blink in confluence governance tools, which delivers low latency trustworthy data at global scale.

Jay Kreps: That's helped them increase developer velocity, improve customer experience, and cut down on operational overhead. Confluent is now a key part of Wix's long-term data platform strategy. And finally, we've been excited to see AI workloads beginning to move towards production in rapidly growing volumes. In 2024, much of the enterprise use of AI was early experimentation with only a few dozen production use cases. This year, we expect production AI use cases to grow 10x across a few hundred customers. A few of my favorite examples from Q2. A public sector organization in New Zealand is deploying AI agents to automate complex regulatory workflows and cut citizen response time from hours to minutes without operational overhead. An astronomy institute is deploying AI agents to process telescope alerts in real time to filter noise and catch rare fast-fading cosmic events before they're lost.

It's helped them increased developer velocity improved customer experience and cut down on operational overhead.

Fluids is now a key part of Wix as long term data platform strategy.

And finally, we've been excited to see AI workloads, beginning to move towards production and rapidly growing volumes in 2020 for much of the enterprise use of AI was early experimentation with only a few dozen production use cases. This year, we expect production in AI use cases to grow tenex across a few hundred customers.

Few of my favorite examples from Q2, a public sector organization in New Zealand is deploying AI agents to automate complex regulatory workflows and cut citizen response times from hours to minutes without operational overhead and astronomy Institute is deploying AI agents to process telescope alerts and real time to filter noise.

Trey or fast fading cosmic events before.

A major.

Jay Kreps: A major Philippine power company is deploying AI agents to interpret real-time alerts, surface critical failures early, and prevent million-dollar outages. An international sports network is generating real-time commentary that adapts to the flow of the game and player performance. Let me go a little deeper on one such use case. We've talked about Notion before when they turned to Confluent after it became clear their data infrastructure couldn't scale or support their AI vision. Since then, they've made Confluent a much more strategic part of their business to accelerate the rollout of new AI capabilities. With over 100 million users, Notion needed a scalable real-time data architecture to power AI-driven search, content generation, and integrations. Their legacy messaging stack couldn't keep up with the volume of product activity, slowing innovation. By adopting Confluent Cloud, Notion built a fully managed event-driven architecture that supports key use cases across their platform.

Specialty is deploying AI agents to interpret real time alerts surface critical failures and prevent outages.

On International Sports Network is.

Maybe some commentary that adapts to the flow of the game and player performance.

Let me go a little deeper on one such use case, we've talked about notion before.

And if I can clear their data infrastructure couldn't scale or support their AI vision. Since then they've made confluent are much more strategic part of their business to accelerate the rollout of new AI capabilities with over 100 million users notion needed a scalable real time data architecture to power AI, driven search content generation and integrations.

So just couldnt keep up with the volume of product.

<unk> innovation by adopting comfort cloud notion built a fully managed event driven architecture that supports key use cases across their platform.

Using our prebuilt connectors, they stream data into snowflake, and Amazon S. III to enable real time analytics and AI workloads stream processing and schema registry insurers that every change in App. This reflected instantly in the vector database keeping mission AI accurate and responsive with confluent notion has tripled platform team productivity reduced <unk>.

Jay Kreps: Using our pre-built connectors, they stream data into Snowflake and Amazon S3 to enable real-time analytics and AI workloads. Stream processing and schema registry ensure that every change in app is reflected instantly in their vector database, keeping Notion AI accurate and responsive. With Confluent, Notion has tripled platform team productivity, reduced operational overhead, and accelerated time to market for AI-powered features. Today, Confluent is the real-time backbone of Notion AI. In closing, while we're continuing to see some near-term consumption headwinds, I remain highly confident in the strength of our business. With our differentiated and complete data streaming platform and strong partner ecosystem, we're well positioned to capture a meaningful share of the $100 billion plus data streaming market. With that, I'll turn it over to Rohan.

Operational overhead and accelerated time to market for AI powered features today, a console, which is the real time backbone of notion AI.

In closing, while we're continuing to see some near term consumption headwinds I remain highly confident in the strength of our business with our differentiated and complete data streaming platform a strong partner ecosystem, we're well positioned to capture a meaningful share of the $100 billion plus data streaming mark with that I'll turn it over to Ron.

Thanks, Jay Good afternoon, everyone and thanks for joining our earnings call on.

Rohan Sivaram: Thanks, Jay. Good afternoon, everyone, and thanks for joining our earnings call. Our second quarter was highlighted by solid top-line growth and continued margin expansion. These results underscore the strength and flexibility of our data streaming platform, helping customers unlock the full value of real-time data across cloud, on-premise, and BYOC environments. Turning to the Q2 results, Q2 subscription revenue grew 21% to $270.8 million and represented 96% of total revenue. Confluent platform revenue grew 12% to $120.3 million, reflecting solid performance in financial services and sustained momentum with our OEM partners. Cloud revenue grew 28% to $150.5 million, representing 56% of subscription revenue, compared to 52% in the year-ago quarter. As Jay mentioned earlier, consumption growth was impacted by continued optimization, with month-over-month trends trailing the same period in prior years.

Our second quarter was highlighted by solid topline growth and continued margin expansion.

These results underscore the strength and flexibility of our data streaming platform, helping customers unlock the full value of real time data across cloud on premise and <unk> environments.

Turning to the Q2 results Q2 subscription revenue grew 21% to $270 8 million and represented 96% of total revenue.

Confluent platform revenue grew 12% to $123 million, reflecting solid performance in financial services and sustained momentum with our OEM partners.

Cloud revenue grew 28% to $155 million, representing 56% of subscription revenue compared to 52% in the year ago quarter.

As Jim mentioned earlier consumption growth was impacted by continued optimization with month over month trends trailing the same period in prior years.

Additionally, an AI native customer has been making a broad based move towards self management of internal data platforms.

Rohan Sivaram: Additionally, an AI-native customer has been making a broad-based move towards self-management of internal data platforms, reducing their Confluent Cloud usage as a result. We continue to support their data streaming needs and have now closed a Confluent platform deal with them in Q3. This represents a significant reduction in total spending with Confluent starting in Q4 and is expected to dampen our Q4 cloud revenue growth rates by low single digits. Turning to the geographical mix of total revenue, revenue from the US grew 15% to $164.3 million. Revenue from outside the US grew 29% to $117.9 million. Moving on to the rest of the income statement, I'll be referring to non-GAAP results unless stated otherwise. While driving top-line growth at scale, we continue to show significant operating leverage in our model.

Reducing the conference cloud usage as a result.

We continue to support their data streaming needs and have now closed a confluence platform deal with them. In Q3. This represents a significant reduction in total spending with confluence starting in Q4 and is expected to dampen our Q4 cloud revenue growth rates by low single digits.

Turning to the geographical mix of total revenue revenue from the U S grew 15% to $164 3 million.

Revenue from outside the U S grew 29% to $117 9 million.

Moving onto the rest of the income statement ill be referring to non-GAAP results unless stated otherwise.

While driving topline growth at scale, we continued to show significant operating leverage in our model.

In Q2 subscription gross margin increased 70 basis points to 81, 5% above our long term target threshold of 80%.

Rohan Sivaram: In Q2, subscription gross margin increased 70 basis points to 81.5%, above our long-term target threshold of 80%. Operating margin increased 570 basis points to 6.3%, exceeding our guidance of approximately 5% and reflecting our continued focus on driving efficiencies across the company. Adjusted free cash flow margin increased 270 basis points to 3.9%. Net income per share was $0.09, using $367.3 million diluted weighted average shares outstanding. Fully diluted share count under the treasury stock method was approximately $380 million. We ended the second quarter with $1.94 billion in cash, cash equivalents, and marketable securities. Turning now to customer metrics. On a year-over-year basis, total customer growth was in line with the average growth rate of the previous four quarters. 20K plus ARR customer count grew approximately 8% to $2,497 and represented more than 95% of ARR.

Operating margin increased 570 basis points to six 3% exceeding our guidance of approximately 5% and reflecting our continued focus on driving efficiencies across the company adjusted free cash flow margin increased 270 basis points to three 9% net income per share was <unk> <unk>.

Using 367 3 million diluted weighted average shares outstanding.

Fully diluted share count under the Treasury stock method was approximately $380 million.

We ended the second quarter with $1 $94 billion in cash cash equivalents and marketable securities.

Turning now to customer metrics on a year over year basis total customer growth was in line with average growth rate of the previous four quarters.

<unk> plus <unk> customer count grew approximately 8% to 2497% and represented more than 95% of IRR.

<unk> plus <unk> customers increased 10% to 1439 and accounted for greater than 90% of Anr.

Rohan Sivaram: 100K plus ARR customers increased 10% to $1,439 and accounted for greater than 90% of ARR. $1 million plus ARR customers grew approximately 24% to $219. New $1 million plus ARR customers continued to come from a wide array of industries and include a conversational AI and automation company, a global food service distributor, a Fortune 500 insurance provider, a cloud-based video platform, and a quality management software company for life sciences. NRR for the quarter was 114%, reflecting ongoing consumption headwinds in our cloud business, while GRR remained close to 90%. Turning now to guidance. Based on current consumption patterns, our outlook for Confluent Cloud assumes month-over-month growth rates for the remainder of the year will remain notably below what we've seen in the same period of prior years.

$1 million plus air customers grew approximately 24% to 290.

New $1 million, plus and our customers continued to come from a wide area of industries and include a conversational AI and automation company a.

Our global and foodservice distributor.

<unk> 500 insurance provider.

How'd based video platform and our quality management software company for life Sciences.

And around for the quarter was 114%, reflecting ongoing consumption headwinds in our cloud business, while <unk> remained close to 90%.

Turning now to guidance based on current consumption patterns are outlook for confluent cloud assumes month over month growth rates for the remainder of the year will remain notably below what we've seen in the same period of prior years, given confluent platforms pipeline visibility in the back half of the year, we are raising our full year growth expectations.

Rohan Sivaram: Given Confluent Platform's pipeline visibility in the back half of the year, we are raising our full-year growth expectations for Confluent Platform. This strength partially helps offset some of the consumption headwinds in our cloud business. For the fiscal third quarter of 2025, we expect subscription revenue to be in the range of $281 to $282 million, representing growth of approximately 17%. Non-GAAP operating margin to be approximately 7% and non-GAAP net income per diluted share to be in the range of $0.09 to $0.10. For fiscal year 2025, we are increasing the low end of our guidance range by $5 million, and we now expect subscription revenue to be in the range of $1.105 to $1.11 billion, representing growth of approximately 20%. Non-GAAP operating margin to be approximately 6%. Non-GAAP net income per diluted share to be approximately $0.36. An adjusted free cash flow margin to be approximately 6%.

We'll confirm platform. This strength, partially helps offset some of the consumption headwinds in our cloud business for.

For the fiscal third quarter of 2025, we expect subscription revenue to be in the range of $2 81 to $2 82 million representing growth of approximately 17%.

non-GAAP operating margin to be approximately 7% and non-GAAP net income per diluted share to be in the range of nine to 10.

For fiscal year 2025, we are increasing the low end of our guidance range by $5 million and we now expect subscription revenue to be in the range of 11052 111 billion representing growth of approximately 20%.

non-GAAP operating margin to be approximately 6% non.

non-GAAP net income per diluted share to be approximately 36.

And adjusted free cash flow margin to be approximately 6%.

For modeling purpose, we expect cloud as a percentage of subscription revenue for Q3 to be approximately 56% and Q4 to be approximately 55%.

Rohan Sivaram: For modeling purpose, we expect cloud as a percentage of subscription revenue for Q3 to be approximately 56% and Q4 to be approximately 55%. Now, I'd like to provide an update on the four strategic pillars of our growth: streaming, DSP, AI, and our partner ecosystem. First, we remain well positioned to lead the core streaming market across on-prem, BYOC, and cloud. Confluent Platform's continued strength has been driven by solid performance in financial services, early traction with partners, and our team's consistent execution. Warp stream consumption exhibited fast growth in Q2, benefiting from customers migrating latency-relaxed workloads from open-source Kafka to drive cost savings while maintaining full control over their data.

Now I'd like to provide an update on the four strategic pillars of our growth streaming DSP AI and our partner ecosystem.

First we remain well positioned to lead the core streaming market across on Prem <unk> and cloud.

Conflict platforms continued strength has been driven by solid performance in financial services early traction with partners and our teams consistent execution, Washington consumption exited fast growth in Q2 benefiting from customers migrating latency relax workloads from open source Kafka to drive cost savings while.

Maintaining full control over their data.

While consumption headwinds persist in our cloud business, we believe our two strategic focus areas along with three targeted double down initiatives will begin delivering meaningful results in a few quarters, helping accelerate our land and expand momentum across customer acquisition use case expansion and DSP monetization.

Rohan Sivaram: While consumption headwinds persist in our cloud business, we believe our two strategic focus areas, along with three targeted double-down initiatives, will begin delivering meaningful results in a few quarters, helping accelerate our land and expand momentum across customer acquisition, use case expansion, and DSP monetization. Second, we are encouraged by the growing traction of our DSP portfolio across both cloud and on-prem environments. As Jay discussed earlier, in just two quarters this year, Flink ARR grew approximately 3x, approaching 10 million, with a fairly even split between cloud and on-prem versions of the product. This validates our strategy of building a complete platform for real-time data everywhere and our ability to take advantage of the shift-left opportunity for stream processing. Third, Confluent's strategic importance in AI is only getting stronger as the world expands from Gen AI to Agentic AI.

Second we are encouraged by the growing traction of our DSP portfolio across both cloud and on Prem environments.

As Jay discussed earlier, and just two quarters. This year <unk> grew approximately three X approaching $10 million with a fairly even split between cloud and on Prem versions of the product.

This validates our strategy of building a complete platform for real time data everywhere.

Ability to take advantage of the shift left opportunity for stream processing.

Total cancun strategic importance and AI is only getting stronger as the world expands from Jenny I to agenda Guy.

Over the past year, we have seen firsthand AI use cases and production growing from chat bot semantic search and content creation to cogeneration and iteration multi agent orchestration Asia and recommendations and much more.

Rohan Sivaram: Over the past year, we have seen firsthand AI use cases in production growing from chatbots, semantic search, and content creation to code generation and iteration, multi-agent orchestration, agent recommendations, and much more. As Jay mentioned, this year, we expect the number of production AI use cases to grow 10x across a few hundred customers. And fourth, we are seeing sustained momentum in our partner ecosystem. In less than a year, we have expanded multiple strategic partnerships, including Jio, SCCC, EY, Databricks, and Infosys, while continuing to build strong partnerships with Accenture, Deloitte, TCS, and more. Partners have stalled well over 20% of our business, and we are capitalizing on this momentum by continuing to invest in our partners to unlock more revenue streams and to further expand our global reach and impact.

As Jay mentioned this year, we expect the number of production AI use cases to grow tenex across a few hundred customers.

And fourth we are seeing sustained momentum in our partner ecosystem and less than a year, we have expanded multiple strategic partnerships, including Gilles.

Triple C E bi data bricks and infosys, while continuing to build strong partnerships with Accenture, Deloitte Dcs and more.

Partnerships.

Well over 20% of our business and we are capitalizing on this momentum by continuing to invest in our partners to unlock more revenue streams and to further expand our global reach and impact.

In closing, we're pleased with our solid top line growth and margin expansion at scale in the second quarter.

Rohan Sivaram: In closing, we're pleased with our solid top-line growth and margin expansion at scale in the second quarter. While there's still work to do in accelerating new use case expansion, we are encouraged by the traction we are seeing across core streaming, DSP, AI, and the partner ecosystem. We believe each of these areas represents a key driver of durable, profitable growth as we look ahead. Now, Jay and I will take your questions.

While there's still work to do and accelerating new use case expansion. We are encouraged by the traction we are seeing across call streaming DSP AI and the partner ecosystem.

We believe each of these areas represent a key driver of durable profitable growth as we look ahead.

Now Jay and I will take your questions.

Thanks Mohan.

<unk> in the Q&A. Please click the raise hand icon, we ask that you limit the Q&A to one question and one follow up.

Shane Xie: Thanks, Rohan. To participate in the Q&A, please click the raise hand icon. We ask that you limit the Q&A to one question and one follow-up. And today, our first question will come from Matt Hepper with RBC, followed by Doja.

And today, our first question will come from Matt Hedberg.

With RPT followed by bloodshed.

Great. Thanks for the question.

You guys for the time today, I guess I wanted to understand a little bit more of the consumption cost consumption optimization trends you talked about and if that's more macro or company specific and now realizing you noted everything that a customer that it sounds like theyre changing some of their consumption, but was there anything recurring.

Matt Hedberg: Great, thanks, Shane, for the question. Thanks, guys, for the time today. I guess, you know, I wanted to understand a little bit more of the consumption optimization trends you talked about and if that's more macro or company specific. And now, realizing you noted there was an AI customer that feels like they're changing some of their consumption, but was there anything recurring in some of these conversations? And how prevalent were they? I think last quarter you mentioned it was a handful of top 20 customers, but just trying to get a sense of how that trended sequentially. Yeah. I would say it's a similar dynamic.

Regulations how.

How prevalent worthy I think last quarter, you mentioned it was a handful of top 20 customers just trying to get a sense of how that trended sequentially.

Yeah, I would say, it's a similar dynamic I do think this is.

Matt Hedberg: You know, I do think this is broadly of the same sort of what we've seen across other companies where customers are happy that plan to be using more data streaming over time, are putting effort into making sure what they've bought, they're getting the most value out of. You know, this hit us a little bit later than some of the other consumption companies, but it's kind of persisted a few quarters longer. And yeah, I would put the AI-native customer in sort of a different category where it's not really an optimization thing at all. They're broadly moving into a different way of kind of operating internally, and I think this is across a number of different vendors, including us. So we were happy to be able to support them with the Confluent Platform deal.

Broadly at the same sort of what you're seeing across other companies where customers are happy.

And to be using mortgage aiming overtime, putting effort into making sure whether they bought they're getting the most value out of them.

This hit us a little bit later than some of the other consumption companies.

And thats kind of persisted a few quarters on that.

And I would put the.

I need a customer in sort of a different category, where it's not really an optimization thing at all there.

Broadly moving into.

A different way of kind of operating internally and I think this is across a number of different vendors, including us. So we were happy to be able to support them.

With the capital platform deal they continue to use our product in more limited use cases, but there is an overall reduction in spending it's definitely a headwind for Q4.

Matt Hedberg: They continue to use our cloud product in more limited use cases, but there is an overall reduction in spend, and it's definitely a headwind for Q4 for cloud. You know, that said, I think a number of kind of positive forces at work here. So if you look at where these customers are going longer term, I think we called out the 31% growth in RPO, and I think that is in large part a bunch of customers upping their overall commitment. That tends to be a headwind to short-term consumption. Bigger commitment means a little bit higher discount levels, but overall kind of gives an indication of the trajectory of their spend. Well, I guess on the other, that's helpful, Jay. And I guess the other thing that you pointed out is just the growth in production AI workloads across a couple hundred customers.

<unk>.

Got it a number of kind of positive forces at work here. So if you look at.

Where these customers are going longer term I think we called out the 31% growth in Rps and I think that is lifestyle bunch customers upping. Their overall commitment that tends to be a headwind to short term consumption and a bigger commitment is a little bit higher discount levels, but.

Overall kind of gives an indication of the trajectory of their staff.

Well I guess on the other that's helpful. Jay and I guess the other thing as you pointed out is.

And just.

The growth in production AI workloads across a couple of hundred customers I guess I'm wondering.

It feels to us like the relevancy of streaming and processing is elevated in the first world.

Matt Hedberg: I guess I'm wondering, you know, it feels to us like the relevancy of streaming and processing is elevated in an AI-first world. How should we think about some of those production workloads eventually positively impacting subscription growth as we think forward over the next year or so? Yeah, yeah, I think it's a very positive force. Ultimately, this is turning into, I think, a really important ingredient in the architecture for AI applications. And it makes logical sense. Like if you want to have some kind of agent that's taking action in the business, it has to have an up-to-date set of context data on what's happening across the business. And so I think we've certainly found ourselves drawn into a set of use cases around that. I think the Notion story is a great one, but there's a number that I called out across different industries and domains.

Should we think about some of those production workload potentially positively impacting subscription growth as we think forward over the next year or so.

Yeah, Yeah, I think it's very positive for US ultimately this is turning into I think a really important ingredient in the architecture for AI applications. It makes logical sense like if you want to have some kind of an agent that's taking action in the business. It has to have an up to date.

Set of context on what's happening across the business and so I.

I think we've certainly found ourselves drawn into a set of use cases around that.

The ocean. The notion story is a great one, but there is a number that I called out across different industries and demands.

I think that's a very positive for us.

Matt Hedberg: So I think that's a very positive force. And not the only one. I think the Flink growth is a huge deal. It's 10 million in ARR, which is very small, but it grew 3x over the last six months. And that's actually very fast growth for something in the infrastructure space. And in many ways, Flink is the crux of that DSP expansion for us, where we feel like going from an important ingredient in the real-time architecture to a full platform, the hard part of that is capturing the application workloads, like the real-time processing. We know what that's about. But the question is, can you build a product that actually does it and that customers can use and benefit from? And I think that's gone quite well, where it's now producing across both cloud and CP and very nice growth rate.

And not the only one I think the fleet growth is a huge deal.

It's $10 million, which is very small.

But it grew three X over the last six months and Thats.

That's actually very fast growth for something in the infrastructure space and in many ways link is the crux of that DSP expansion for us where we feel like going from an important ingredient in a real time architecture to a full platform the <unk>.

And part of that is capturing the application workloads like the real time processing, we know what thats about.

But the question is can you build a product that actually does it.

And the customers can use and benefit prominent I think that's gone quite well, where its now producing across both cloud and CP and very nice growth rate, so not not something that determines the overall number at this point, but we're very excited by the early progress last year.

Matt Hedberg: So not something that determines the overall number at this point, but we're very excited by that early progress and want to see it continue. Thanks, Jay. All right, thanks, Matt. We'll take our next question from Brett Zelnick with Deutsche Bank, followed by Morgan Stanley.

Thanks, Jeff.

Alright, Thanks, Matt we'll take our next question from Brad Zelnick with Deutsche Bank, followed by Morgan Stanley.

Okay. Thanks, so much Shannon and nice to see you guys.

Jay Kreps: Thanks so much, Shane, and nice to see you guys. Jay, a lot of exciting things happening, a lot of good data points coming out of this quarter, but at the same time, you still continue to be surprised by this optimization activity that's occurring with your large customers. You then talked about Ryan McMahon 90 days in and the two key focus areas and operational enhancements that he's making. I was just wondering, is that in relationship to what's happening with large customers? Or is that, and the optimization that you're seeing, or is that completely separate?

<unk> got a lot of exciting things happening a lot of good data points coming out of this quarter, but at the same time you still continue to be surprised by this optimization activity that's occurring with your large customers. You then talked about Ryan Mcmahon 90 days.

The two key focus areas and operational.

The enhancements that he's making I was just wondering if that in relationship to what's happening with large customers or is that any optimization that youre seeing or is that completely separate and can you maybe just.

Slowdown and explain a little bit why you're confident that these investments that youre going to make in the coverage ratios across aes <unk> and post sales support as well as the build out of the DSP specialist team is really going to make a difference and over what timeline yeah. Yeah. It's.

Jay Kreps: And can you maybe just slow down and explain a little bit why you're confident that these investments that you're going to make in the coverage ratios across AEs, SEs, and post-sale support, as well as the build-out of the DSP specialist team, is really going to make a difference and over what timeline? Yeah, yeah, it's a good question. So yeah, I would think of it this way. There's some amount of optimization customers are doing at any given time. Right? I think that's been exaggerated in recent quarters. Right? And then when you think about what's the balance, the balance of growth is new use case additions, minus optimizations. And when we think about what we're in control of, it is these new use case acquisitions. Are we going out and winning the new workloads? Are we making sure we're connecting with those?

Great question. So, yes, I would think of it. This way there is some amount of optimization customers are doing at any given time right I think thats been.

Exaggerated.

In recent quarters right.

And then when you think about whats the balance the balance of growth is new use case additions minus optimizations and.

When we think about what we're in control of is these new use case acquisitions are we going out and winning the new workloads are we making sure we're connecting with those that were bringing in.

The right customers and so.

Jay Kreps: Are we bringing in the right customers? And so that's obviously where our focus is. I think we've seen very good early results from these changes that Ryan has made. On some of these alignment things and the SE ratio, this was one of the changes we made both to get good market costs in line and through our consumption change. I think it just didn't quite work the way we wanted. We were able to change to a better coverage model without negative cost impact. And I think that's paid off in some of the progression of streaming projects that we've seen already. So I called this out just like we measure the early stages of this in terms of kind of late-stage pipeline. How is that trending? And this is consumption pipeline, so it's actual customer workloads heading to production. You know, that's up quite substantially.

That's obviously, where our focus is the yes.

I think we've seen very good early results from these changes.

Ryan has made.

On Chinese alignment things in the <unk> ratio.

This was one of the changes we made both to get go to market costs in line and through our consumption change I think just didn't quite work. The way. We wanted we were able to change change to a better coverage model without negative cost impacts and I think thats paid off in some of the question of streaming projects at <unk>.

<unk> already so I called this out just like we measure the early stages of this in terms of.

Our late stage pipeline, how is that trend data and this is consumption pipeline to actual customer workloads heading to production that's up quite substantially.

Is it greater than 40%.

Jay Kreps: I think I said greater than 40% Q1 to Q2. And I think that's a good result that came out of some of the operational improvements there. So that's the early indicator. Now, obviously, we don't count our chickens till they're hatched, but those are the things we look at when we think about what the kind of forward momentum is. Right. Thank you. That's helpful, Jay. And maybe Rohan, for you, just as we think about your messaging coming out of last quarter, again, surprised coming out of Q2 as well, what can you tell us about the approach to guidance and whether it's in the form of conversion rates or anything else to help us really appreciate what is expected in the back half and how much this may or may not be de-risked at this point? Thank you very much. Yeah, Brad, thanks for your question.

Q1 to Q2 and I think that's a good result that came out of some of the operational improvements. There. So that's the early indicators now obviously, we don't count our chickens till they're hatched, but those are the things we look at when we think about what the kind of forward momentum is great. Thank you that's helpful. Jay and maybe real hard for you just as we think about your mess.

And coming out of last quarter again surprised coming out of Q2 as well what can you tell us about the approach to guidance.

Whether it's in the form of conversion rates or anything else to help us really appreciate what is expected in the back half and how much this may or may not be and derisked at this point. Thank you very much.

Yes.

Ryan Thanks for your question.

Historically as I've said in the prior call as well as typically seen quick assumptions rebound after say a quarter of optimization.

Jay Kreps: Historically, as I've said in the prior call as well, we've typically seen a quick consumption rebound after, say, a quarter of optimization. You know, best example, recent example is Q2 to Q3 of last year. Specifically, what we saw in the quarter was the larger customer is optimizing. That continued. And the adoption of new use cases was more measured. Given the dynamic of Q2 and Q1, what we are doing right now for cloud is we are primarily assuming the cloud outlook for month-over-month growth rates to be notably below what we've seen in the same period of prior years. So that's what we've done for cloud. So despite this dynamic, I want to take a step back and just talk a little bit about the total guidance. We're actually raising our fiscal year '25 subscription revenue guide at the midpoint.

The Best example of a recent example is Q2 to Q3 of last year.

Typically what we saw in the quarter was the larger customers optimizing that continued.

The adoption of new use cases, where more was more measured given the dynamic of Q2 and Q1, what we are doing right now for cloud.

We're primarily assuming the cloud outlook per month over month growth rates to be notably they know what we've seen in the same period of prior years.

So that's what we've done for cloud.

Despite this dynamic I want to take a step back and just talk a little bit about the total guidance.

Raising our fiscal year 'twenty five subscription revenue guide at the midpoint and what's supporting this is the strength in our <unk> business, we have visibility into second half pipeline and.

Jay Kreps: And what's supporting this is the strength in our CP business. We have visibility into second-half pipeline. And also on the cloud side, as Jay briefly touched on, we are seeing a bunch of good yields. First of all, the Flink momentum. When you think about Flink, it has approximately tripled in the first six months of the year, closing in on 10 million in ARR. The late-stage pipeline projection is we saw a sequential improvement of greater than 40%. And finally, you know, some of our customers committing to larger multi-year deals following periods of optimization. That shows up in our RPO numbers. So when you kind of take all of this together, the backup guidance is for cloud. You know, we're not assuming month-over-month growth rates. It's actually notably below historical averages for same periods in prior years. For platform, we have visibility into our pipeline.

Also on the cloud side as Jay touched on we are seeing a bunch of windshields first of all the fleet momentum when you think about <unk>. It is approximately tripled in the first six months of the year closing in on $10 million in IRR.

<unk> stage pipeline projection.

And so we saw a sequential improvement of greater than 40%.

And finally, some of our customers committing to larger multi year deals following periods of optimization that shows up in our RVO numbers. So when you kind of take all of this together our back half guidance is for cloud, we're not assuming month over month growth rates, its actually notably below historical averages pharmacy.

As in prior years, our platform, we have visibility into our pipeline.

And for the cloud Green shoots it's like a portfolio approach.

Jay Kreps: And for the cloud green shoots, it's like a portfolio approach. You know, there are upside levers in that that we will realize, like Jay said, we're not counting our chickens before they hatch. Thank you, Rohan. Thanks, Brad. We'll take our next question from San Jason with Morgan Stanley, followed by Bernstein. Thank you for taking the questions. Jay, I wanted to go back to some of the go-to-market changes that you guys have been rolling out over the past couple of years, particularly the move to compensating sales reps on incremental consumption. Just how has that been going and to what extent is that still a friction or non-friction point when it comes to driving incremental cloud consumption growth? Yeah, I think overall it's gone well.

Upside levels and that we will realize like Jay said theyre not counting our chickens before they hatch.

Thank you Ron.

Okay.

Thanks, Brent what's in our next question from Sanjay <unk> with Morgan Stanley followed by Bernstein.

Thank you for taking the questions. So I wanted to go back to some of the go to market changes that you guys have been rolling out of the past couple of years, particularly the move to.

Compensating sales reps on incremental consumption, just how has that been going and to what extent is that still a friction or non friction point when it comes to driving incremental cloud consumption growth.

Yes, I think overall, it's gone well I think it was a critical change for us just to be aligned to what the company is trying to drive and to actually be able to unlock that use cases being able to have compensation on some of the DSP offerings that might get added on initially after year commit.

Jay Kreps: I think it was a critical change for us just to be aligned to what the company is trying to drive and to actually be able to unlock the use cases, be able to have compensation on some of the DSP offerings that might get added on initially, even after you commit. So there's a whole set of motivators that I think it's actually helping with. There's certainly been adjustments we've made along the way, including the things I called out in the script to try and make sure we're really optimizing for it. So I think that those will help us realize even more results from it. Awesome. And then on Flink, that we noticed in our customer conversations that Flink was sort of building them as well. I know that Flink started as a part of Confluent Cloud.

The whole set of motivators.

It's actually helping lift.

There's certainly been adjustments, we've made along the way.

Including the things I called out in the script.

To try and make sure we're really optimizing for it so.

So I think that those will help us realize even more results from it.

And then on sling on that.

Notice in our customer conversations on that Frank was.

Sort of building momentum as well.

I know that things started as a part of conflict cloud.

It was in the second half of last year, I mean last year, you sort of introduced at Intel <unk> platform with that like the unlock and can you sort of explain to us like we think about the flank opportunity why is it such an even balance between cloud and non package.

Jay Kreps: I think was it the second half of last year or middle of last year? You sort of introduced it into Confluent Platform. Was that like the unlock? And can you sort of explain to us, like we think about the Flink opportunity, why is it such an even balance between cloud and on-prem? Yeah, both good questions. So yeah, you know, there's been a build-up on Flink because we had to, because of German law, announce one of the acquisitions we made after we were doing this. We had to tell people we were doing something with Flink well before we had the product out. It did get into the market mid-last year. Obviously, for us, then we have to ramp it across the different cloud providers, open it up for the kind of private networking types that certain customers have to really get the full unlock.

Yes, both good questions so yet.

It's been a.

Buildup on <unk>, because we had to because of German law announce one of the acquisitions, we made actually is to.

To help people doing something with <unk>.

Before we had the product out.

<unk> get into the market.

Mid last year.

Obviously for us and we have to ramp it across the different cloud providers open it up for the kind of private networking types at certain customers have to really get the full on market than we've seen.

Post that great monetization results and I think that will increase future unlocks coming there.

Jay Kreps: And then we've seen post-fact great monetization results. And I think that will increase. There's future unlocks coming there. You know, this area of data processing, people know what it is. They know they want it. They know they need to do it in real time. You know, it's a question of really getting something that's super solid that does everything a modern platform does, but does it continuously and in real time. So I think it's been exciting to kind of get to that point with customers. You know, that ramp has been quite steady. So if you look at cloud, you know, just the growth quarter over quarter, but if you were to look into it month over month, it's just a very steady ramp. The reason for that is it is a serverless offering. So adopting Flink costs you nothing.

This area of data processing people know what it is they know they want it.

They need to do it in real time.

But really getting something that's super solid it does everything a modern platform does what it does it continuously and in real time.

I think it's been exciting to kind of get to that point with customers.

That ramp has been quite steady so if you look at cloud.

Just the growth.

Quarter over quarter, but if you were to look into it month over month is just steady ramp. The reason for that is it is a server list offering so adopting flink costs you nothing each incremental core workload that you are kind of adding that.

Jay Kreps: You know, it's each incremental query or workload that you're kind of adding that's building up that consumption. You know, and that is the nature of that business. So kind of building that momentum then becomes a very powerful force, even in customers that have adapted their continuing to add queries and grow their consumption. CP Flink is a little different, where the tendency is you're kind of pre-deploying, right? So it will come in bigger chunks. Like CP, it will tend to appeal to some of these larger customers that have data centers, has a little bit more of an opportunity to kind of migrate in-place workloads. So for that reason, it tends to be the smaller number of customers and capturing a bit more in each chunk.

Thats building up that consumption.

And that is the nature of that business.

So kind of building that momentum then becomes a very powerful force even in customers that have adopted there continuing to add quarries and grow their consumption.

<unk> is a little different where the tendency as youre kind of pre deploying right. So that will come in bigger chunks like CPA will tend to appeal to some of these larger customers that have data centers.

Is it a little bit more of an opportunity to kind of migrate in place workloads. So for that reason it tends to be the <unk>.

Mahler number of customers and.

Capturing a bit more.

And each chunk, so little bit different between both but the kind of net net is.

Jay Kreps: So a little bit different between both, but the kind of net-net is we're contributing, both are contributing, we're serving customers across both, and both are actually growing very nicely between the two. Awesome. Thank you. Yeah. Thanks, Sanjay. We'll take our next question from Peter Weave with Bernstein, followed by William Blair. Thank you and appreciate all the detail you've been giving, particularly around some of the optimization that's been going on.

We're contributed both are contributing we're serving customers across both and both are actually growing very nicely between the two.

Awesome. Thank you.

It extended we'll take our next question from Peter meet with Bernstein, followed by William Blair.

Thank you and appreciate all the detail you've been giving particularly around.

Some of the optimization thats been going on one of the things that struck me is we've been focused on these big customers, but I guess also what I'm, taking a look at some of the customer bands that you report.

Jay Kreps: You know, one of the things that struck me is we've been focused on these big customers, but I guess also when I'm taking a look at some of the customer bands that you report, you know, the kind of 20 to 100K size customers, which I would think would be kind of your fastest growing kind of future cohort that will hopefully graduate into those 100K plus million plus customers over time, actually has been probably the weakest of any of those cohorts this last quarter.

The kind of 20 to 100, K sized customers, which would I would think would be kind of your fastest growing kind of future cohort.

That will hopefully graduate into those 100 K plus million.

Plus customers over time actually has been probably the weakest.

Any of those cohorts this last quarter, how should we think about that kind of incremental.

Jay Kreps: How should we think about the kind of incremental number of customers being added to that segment as a kind of a future signal for growth and perhaps at some of the sales initiatives that are going on that are going to be trying to drive a lot more customers into that kind of early phase that turn into the very big customers over time? Yeah, yeah. So if you look across the customer bands, as you say, kind of strength in 100K plus, strength in million dollar plus, lighter on the 20K plus. And we think that's a key metric. So that is a point of focus for us. Heading into this year, I do think we made some changes that lost some of the focus there. In some of what I described, we are trying to make sure that we're nailing that.

Number of customers being added to that segment is kind of a future signal for <unk>.

Growth and perhaps at some of the sales initiatives that are going on that are going to be trying to drive a lot more customers into that kind of early.

Phase that turn into the very big customers over time.

Yeah Yeah.

So if you look across the customer bands.

As you said kind of strengthening 100, K plus strength of $1 million plus lighter on the 20 <unk> plus.

And we think that's a key metrics. So that is a point of focus for us heading into this year I do think we made some changes at <unk>.

Some of the focus there and some of what I described we are trying to make sure that we're nailing that so in particular.

<unk> CSP takeouts.

Jay Kreps: So in particular, I do think these CSP takeouts that I described are an awesome opportunity for that. That's an area where we're seeing a lot of early success. There are a lot of commensurate groups out there that have adopted one of the offerings from the cloud providers. And the reality is those offerings have never been great. But increasingly, as our product portfolio has kind of filled out, we have something that's not just a better offering, but it's actually a better deal. And so you kind of have something that's more complete, better performance, and kind of better price point with freight and these enterprise clusters warp stream. And so early results from that are quite good. And we think that that particular program and a focus on those lands is a great way of kind of getting out to more breadth.

Fiber and awesome opportunities.

Area, where we're seeing a lot of early success there are.

A lot of customers out there that adopted <unk>.

<unk> from the cloud providers and the reality is those offerings I've never been great.

But increasingly as our product portfolio is kind.

Kind of filled out we have something thats, not just a better offering but is actually a better deal.

And so you kind of have something that's more complete better performance and better price point with freight and these enterprise clusters, where upstream and so early results from that are quite good and we think that that particular program and a focus on those lands is a great way.

Now kind of getting out to more breadth.

And is there anything that we should read into that around kind of increased churn levels I noticed some of the commentary changed around.

Jay Kreps: And is there anything that we should read into that around kind of increased churn levels? I noticed some of the commentary changed around gross revenue retention. I think historically you've said, hey, it's above 90%. This quarter it said it remains about 90%. I didn't know if that was like an increased churn and that was being seen in that customer segment or I'm just reading too much into that commentary. Yeah, I wouldn't attribute too much to that segment overall. I think it's mostly about really driving the lands in that segment as the biggest contributor. Okay. Yeah, I think you've got that at all, Ron. Thank you. I think you saw that, Jay. Great. We'll take our next question from Jason Ader with William Blair, followed by Mizuho. Yeah, thanks, Shane. Can you hear me okay? Yeah, loud and clear. Okay.

Gross revenue retention I think historically, you've said hey, it's above 90% this quarter it said.

Remains about 90% I didn't know if that was like an increased churn and that was being seen in that customer segment, where im just reading too much into that commentary.

Yeah I wouldn't attribute.

Too much to that segment overall I think it's mostly about really driving the lands in that segment is the biggest contributor.

Yes. Thank you.

Got it all wrong.

I think the southern Virginia.

Great well take our next question from Jason Ader, with William Blair, followed by Mizuho.

Yeah. Thanks, Shane can you hear me okay, yes.

Yes, that's clear okay.

J J I understand the challenges in predicting that customer consumption patterns and definitely appreciate the transparency in what's happening at the ground level.

Jay Kreps: Jay, I understand the challenges in predicting the customer consumption patterns and definitely appreciate the transparency on what's happening at the grand level. But I think we all expected some improvement in the business following the refinement in the sales comp model last year. The broadening of the product set and the pretty significant broadening of the product set over the last year and a half or so. And then a greater amount of AI adoption where we're obviously getting closer to a tipping point. Now it feels like we're kind of back to square one a little bit and waiting for things to get better. So why should investors believe that this time is different? Yeah, yeah, and it's a fair question. You know, I think a lot of the things we said would contribute are starting to do that.

But I think we all expected some improvement in the business following the refinement and the sales comp model last year, the broadening of the products have to be pretty significant broadening of the product set over the last year and a half or so and then greater amount of AI adoption, where we're obviously getting closer to a tipping point now it feels like it feels like we're kind of back to square, one a little bit and waiting for <unk>.

Things to get better so why should investors believe that this time is different.

Yeah, Yeah, it's a fair question.

I think a lot of the things. We said we would contribute are starting to do that I think we shared a little bit of that right. We've talked about some of the ESP offerings I think we shared a bit about what's happening with link.

Jay Kreps: I think we shared a little bit of that, right? We've talked about some of the DSP offerings. I think we shared a bit about what's happening with Flink. I think we've talked a little bit more quantitatively about some of these AI use cases and what we're seeing there. You know, there is a headwind with some of the existing large customers and optimization. I do think that these things that are smaller but growing fast may eventually do predominate as they grow. But to cancel each other out, they have to get to the scale that matters. So in those positive tailwinds, I would include those things I just mentioned.

I think we've talked a little bit more quantitatively about some of these AI use cases, and what we're seeing there.

There is a headwind with <unk>.

Some of the existing large customers and optimization I do think that these things that are smaller but growing fast. They eventually do predominantly as they grow.

Cancel each other out they have to get to the scale that matters. So in this positive tailwind I would include those things I just mentioned I would include the buildup.

Appealing commitments in cloud, which I think is a positive sign.

Jay Kreps: I would include the build-up of RPO and commitments in cloud, which I think is a positive sign in terms of what customers' intentions are over time, as well as that overall progression of pipeline, which I do think is a reflection of kind of the focus on this within our sales organization. Gotcha. I mean, it's got to be frustrating for you. Yeah, well, there's different forces. I mean, if you step back, right, I think Confluent has a fantastic position in the data landscape. You know, if you ask, is there going to be more streaming in three years or less, there's going to be a lot more. And kind of our hand on the product side has gotten better. So yeah, it's frustrating when you have a dynamic with a subset of customers.

In terms of what customers intentions are over time.

As well as that overall progression of pipeline, which I do think is.

A reflection of kind of the focus on this within our sales organization.

Gotcha.

It's got to be frustrating for you.

Well, there's different forces I mean, if you step back right I think confidently has a fantastic position in the data landscape. If you ask me is there going to be more streaming in.

Three years, so Alaska is going to be a lot more and kind of our hand on the product side has gotten better.

Yes, it's frustrating when you have the dynamic with a subset of customers.

But nonetheless, I do you think the bigger picture I would say.

Jay Kreps: But nonetheless, you know, I do think the bigger picture, I would say I'm as excited about where we're at as ever. And yeah, I think there's a lot of good things coming out of the business. All right, one quick follow-up for Rohan. Rohan, can you help us on the NRR outlook? It dipped to the 124. I guess that's the consumption driving that. Do you think it will continue to dip, just given some of your comments on the back half? Yeah, Jason, you rightly called it out. You know, just for the broader group of folks here, when you think about our cloud business, NRR and GRR are essentially calculated based on the last three months' consumption on an annualized basis. As a result, just it has an outsized impact. The current quarter consumption typically has an outsized impact on both these metrics.

As excited about where we're at as ever and I think there is a lot of good things coming out of the business.

One quick follow up for Rob Rowe Han can you help us on the MLR outlook.

To the 124 I guess, that's the consumption.

Driving that.

Do you think it will continue to depth just given some of your comments on the back half.

Yes, Jason you rightly called out.

As far as the broader group of folks here when you think about our cloud business and our LNG are essentially calculated based on the last three months consumption on an annualized basis.

As a result.

It has an outsized impact the current quarter consumption typically has an outsized impact on both these metrics.

In line with our cloud second half outlook should we expect to see near term pressure on both the metrics, having said that I'll tell you that.

Jay Kreps: So in line with our cloud second-half outlook that we shared, we expect to see near-term pressure on both the metrics. Having said that, I'll tell you that, you know, all the focus that Ryan's driving on the go-to-market side, the inter-double-down initiatives, coupled with the green shoots mentioned earlier, they will be tailwinds. So there are a bunch of puts and takes to the NRR as we look at backup of the year and beyond. Thanks, you guys. Good luck. Thanks, Jason. We'll take our next question from Gray Moskowitz with Mizuho, followed by Choice Securities. Great, thanks, Shane. So Jay, I'm curious to hear your thoughts on your former company's decision to move away from Kafka due to perceived scalability and operational challenges.

Although focused at Ryan's driving on the go to market side <unk> initiatives, coupled with the Green shoots mentioned earlier they will detail ways. So there are a bunch of puts and takes as we look at back half of the year and beyond.

Thank you guys. Good luck.

Thanks, Jason and I will take our next question from Gregg Moskowitz with Mizuho, followed by choice Securities.

Great. Thanks, Thanks, Shane J I'm curious to hear your thoughts on your former company decision to move away from Kafka due to perceived scalability and operational challenges just given your history and your very deep knowledge of Costa and the broader streaming space your perspective on that would certainly be helpful.

Jay Kreps: You know, just given your history and your very deep knowledge of Kafka and the broader streaming space, your perspective on that would certainly be helpful. Yeah, you know, this is kind of an internal system inside of LinkedIn where I used to work 10 years ago. You know, yeah, I think it's kind of a non-issue. I mean, LinkedIn has very custom internal infrastructure. You know, they actually made this change a long time ago. I think they only talked about it recently. You know, their internal thing is very tied to their infrastructure and not open source, so it doesn't represent any kind of competitive threat to Confluent or anything like that. In terms of why they've done that, you know, they've built their own custom database. They've built a lot of custom things at this point.

Yeah.

Just kind of internal system inside of linked in wear to work.

10 years ago.

Yeah, I think it's kind of a non issue.

<unk> has very custom internal infrastructure.

They actually made this.

Change a long time ago, I think you already talked about it recently.

There are internal thing is very tied to their infrastructure and not open source. So it doesn't represent any other competitive threat to.

Confluence or anything like that in.

In terms of why they've done that.

Build their own custom database they built a lot of custom things at this point.

They're not even running in the cloud, even though they're owned by Microsoft.

Jay Kreps: You know, they're not even running in the cloud, even though they're owned by Microsoft. So I think, you know, they have a bit of an in-house culture, which I think probably is a driver for some of this stuff. Super helpful. And then just either for Jay or for Rohan. So you know, when I look at Confluent Cloud, certainly it was a shining star and has been a shining star of the Confluent growth story for quite some time. Obviously, the growth more recently for this segment is slowing down a fair amount. Any concerns that there may be competitive and/or pricing issues contributing to some of the incremental challenges that Confluent Cloud is experiencing right now? Or are you just not seeing that when it comes to win rates and when it comes to discounting? Yeah, it's a great question.

They have a bit of an in-house culture, which I think probably as a driver for some of this stuff.

Super Helpful. And then just either for <unk>. So when I look at comprehend cloud certainly it was a shining star and has been a shining star of the consequent growth story for quite some time, obviously the growth more recently for this segment is slowing down a fair amount any concern that there may be competitive and our pricing issues contributing to <unk>.

The incremental challenges that coupling clouded experiencing right now or are you just not seeing that when it comes to win rates and when it comes to discounting.

Yes, it's a great question. So yeah, we haven't seen a huge change in the competitive dynamic overall, if anything I think our hand versus some of the cloud provider offerings has strengthened.

Jay Kreps: So yeah, we haven't seen a huge change in the competitive dynamic overall. You know, if anything, I think our hand versus some of the cloud provider offerings has strengthened. And you know, that's a focus area for us to go after those. You know, on the pricing, we have introduced offerings that open up, you know, a set of workloads, the freight and enterprise clusters. We're starting to see, you know, I think very strong early success with those. It always takes time for these new things to really go capture the opportunity. But I do think that that's a big opportunity for us to get out into that. Thanks, Jay. Yeah, thanks. We'll take our next question from Millard Dunk with Choice Security, followed by TD Cowan. Millard, you're still on mute. All right, why don't we come back to you? We'll go to Derek first.

And that's a focus area for us to go after those.

On the pricing, we have introduced offerings that open up.

A set of workloads, the freight and enterprise clusters, we're starting to see I think very strong early success with us. It always takes time for these new things to really go capture the opportunity, but I do think Thats big.

Big opportunity for us to get out.

Great. Thanks, Hey, yes.

Within our next question from Millet jump with curious security followed by TD count.

Yes.

You're still on mute.

Alright, why don't we come back to you we'll go to Derek first.

Okay.

Great. Thanks, guys I guess to start with you Jay.

Jay Kreps: Great, thanks, guys. I guess to start with you, Jay, could you give us a sense as to how much structural change we should be expecting from the field realignment efforts and really how long you think that these realignments will take to implement and when we should be thinking about them driving some meaningful dividends? Yeah, I think we're starting to see, you know, good forward momentum there already. You know, there have been changes within the team, and you know, I think those are ultimately positive things. Ultimately, when we bring in a new leader, we want them to change the things. It hasn't been a complete, you know, reorg of everything. You know, we're broadly organized in the same way. But I do think coming into this year, we saw a few things that weren't quite right and have made adjustments around them.

Can you give us a sense as to how much structural change we should be expecting from the <unk>.

Field realignment efforts and.

Really how long do you think that these these realignments will take to implement and when we should be thinking about them driving some meaningful dividends.

Yeah, I think we're starting to see good forward momentum there already.

There have been changes in the team and I think those are ultimately positive things.

Ultimately when we bring in a new leader, we want them to change the plan Hasnt been a complete rework of everything we're broadly or crashed in the same way, but I do think coming into this year. We saw a few things that weren't quite right that made adjustments around them.

And then kind of related and maybe for a hot button.

Jay Kreps: And then kind of related, I mean, and maybe for Rohan, but you just looking at your net new customers, the million-dollar net new customers have been really strong. The net new on the 100K has been pretty weak in the quarter and kind of directionally under pressure for the last year or two. But what should we take away from these numbers? Has there been a go-to-market shift more at the large deal front, or are some of these realignment efforts designed to kind of drive better activity at that 100K plus? Just curious how you're thinking about the direction of these numbers. Yeah, I can take some of that and Rohan can chime in as well.

Just looking at your net new customer the million dollar net new customers have been really strong.

The net new on the 100 K has been pretty weak in the quarter and kind of directionally under pressure for the last year or two but what should we takeaway from these numbers has there been a go to market shift more at the large deal front or.

Or are some of these realignment efforts designed to kind of drive better activity at that 100, K plus just.

Just how youre thinking about the direction of these numbers.

Yes, I can take some of that and Ron can chime in as well I do think as I said on the prior answer.

Jay Kreps: You know, I do think, kind of as I said on the prior answer, I do think this is one of the points we want to address in terms of kind of the alignment between some of the STRs, SEs, how they're going after, what accounts they're targeting. You know, I do think we've probably had more focus on some of the existing customers and said that, you know, really make sure we're landing the right folks is critical. I think the CSP takeout opportunity is a key initiative there where we think there's a good opportunity of things we haven't paid as much attention to that are quite right. So we would like to see some results in that, you know, over the coming quarters. And Rohan, I'm sorry, I think you're--welcome to jump in there. Yeah, I'll probably just add two points, Derek.

We think this is one of the points, we want to address in terms of kind of the alignment between some of the SCR is sce's how are they going after what accounts they are targeting.

I do think we probably add.

More focus on some of the existing customers instead of the rear.

Make sure we're landing the right folks is critical I think the.

CSP takeout opportunity is a key initiatives there, where we think there's a good opportunity and things we haven't paid as much attention to that are quite right. So we would like to see some results from that.

Coming quarters.

And Ron inside.

Now for you to jump in there.

Yes, I would probably just add two points Derek the <unk> one of the things that we focus on internally is from top of the funnel.

Jay Kreps: The first is one of the things that we focus on internally is from top of the funnel to million dollars, how that customer cohort is progressing. And you know, some of the focus areas that Ryan's driving, that's going to just fine-tune that motion even more. So that's one aspect of it. The second aspect of it on the larger customer front, our DSP penetration is a huge opportunity. And that's something that we're very focused on. What I can tell you is, like with respect to our larger customers, we are having conversations and a substantial majority of them with respect to having some form of DSP continued usage. So in addition to what Jay said, those are two focus areas that we expect to drive even better performance, not only on the bottom of the funnel, but also on the top of the funnel. Understood. Thank you.

How that customer orders, but let's see.

Some of them.

Okay asset lines driving that so let me just fine tune that motion even more so that's one aspect of it the second aspect of it in the larger customer front, our ESP penetration is a huge opportunity and that's something that we're very focused on what I can tell you is like with respect to our larger customers, we are having conversation and substantial.

Majority of them with respect to having some form of DSP continued usage. So in addition to what Jay said those are two focus areas that we expect to drive even better performance not only on the bottom of the funnel, but also on the downside.

Understood. Thank you alright, Thanks, Derek will go back to Millar and try one more time alright can you hear me now.

Jay Kreps: All right, thanks, Derek. We'll go back to Millard and try it one more time. All right, can you hear me now? Loud and clear. Loud and clear. All right, thank you very much for taking the question. Maybe just starting with the large AI customer that you all mentioned in the prepared remarks. You know, moving back to Confluent Platform, I guess I'm curious, like is there an architectural advantage to supporting AI with Platform? And do you anticipate realizing more of the AI opportunity on Platform now after seeing this activity? No, I don't think it's a structural thing. I'd say it's unique to the circumstances of this customer. You know, ultimately, the AI opportunity is kind of across both Platform and Cloud. You know, I think it's worth separating out selling into AI companies.

Alright, Thank you very much for taking the question.

Maybe just starting with the large AI customer that you all mentioned in the prepared remarks.

Moving back to top off platform I guess I'm curious like is there an architectural advantage to supporting AI with platform and do you anticipate realizing more of a an AI opportunity on platform now fresenius activity.

No I don't think it's a structural thing I'd say is unique to the circumstances of this customer.

The ultimately the AI opportunity is kind of a cross both platform and cloud the.

Yeah.

I think it's worth separating out selling into AI companies. They are there is obviously a set of startups that are very predominant in the cloud and then you probably read some of these larger companies are making investments.

Jay Kreps: There, there's obviously a set of startups that are very predominant in the Cloud. And then, you know, you try to read some of these larger companies are making investments in on-premise data centers and more self-management. So on, it's more determined by the operations of the company than the industry or use case. And then when you think about the larger opportunity with AI, I do think it is the enterprise use cases deploying AI in their business. And that is, again, you know, it depends on where that is happening. You know, much of it is in the Cloud, but you know, there's also large financial services organizations doing big, interesting things in their own data centers. And so, you know, we'll see it across both sides. Okay. And maybe just this is a follow-up on kind of Rohan's commentary on the DSP traction that you're seeing.

MS data centers in more self management. So I think it's more determined by the operations of the company than the industry or use cash.

And then when you think about the larger opportunity with AI do you think it is the enterprise use cases deploying AI in their business and that is again.

Depends on where that is happening.

Much of it in the cloud, but there's also a large financial services organizations doing interesting things in their own data centers and so you'll see it across both sites.

Alright.

And maybe just as a follow up on kind of broader commentary on the DSP traction that youre seeing obviously optimization headwinds of cloud on this a little bit but on.

Jay Kreps: Obviously, optimization headwinds are clouding this a little bit. But, you know, on the one hand, there's really promising DSP uptake that you all are talking about. But at the same time, we continue to see Cloud decelerate despite that contribution. So I'm wondering if you could unpack that a little bit more. Like, are we seeing customers getting cost efficiencies on the streaming side that are then being applied towards the new capabilities? Or is it something where there are actually less streams being created and they're just applying DSP to those? Yeah, I think this is ultimately, you know, an efficiency question, right? So we've been through this in the past. And I'd say it's broadly the same pattern of things, right? There's customers that are making kind of architectural changes to try and condense their workloads and squeeze more out of the infrastructure they're using.

On the one hand, a really promising DSP uptake that you all are talking about but at the same time, we continue to see cloud decelerated. Despite that contribution. So I'm wondering if you get unpack that a little bit more like are we seeing customers getting cost efficiencies on the streaming side that are then being applied towards the new capabilities or is it something where.

We're actually less screens being created and their discipline.

Yeah I think this is ultimately in efficiency question right. So we've been through this in.

In the past I would say is broadly the same pattern of things right. Those customers that are making kind of architectural changes to try and condense their workloads and squeeze more out of the infrastructure they are using.

That's a natural thing you would do in almost any kind of cloud.

Jay Kreps: That's a natural thing you would do with almost any kind of Cloud offering. And that's certainly what we're seeing. The DSP growth, I think, is actually separate and super promising. You know, what you need is for that number to get big enough that it outweighs, you know, effectively these very large Kafka installations. You know, not exclusively, but certainly a number of them in some of these tech companies that are working very hard to cut Cloud costs across the board. And so you kind of have two forces in the business. I will say, you know, these optimizations, you only optimize so much, right? So it kind of trickles off. Whereas the DSP growth, I think, is in the early days of a sustained run.

Offering and that's certainly what we're seeing the GSP growth I think is actually separate and Super promising you. What you need is for that number to get big enough.

It outweighs effect of these very large kafka installations.

Yeah, not exclusively but that's certainly a number of them in some of these tech companies that are working very hard to cut cloud costs across the board and so you kind of have two forces in the business I will say the optimization you only optimize so much right. So kind of trickled software as the DSP growth I think is in the early days.

Sustained run so when I talk about just kind of overall at a ton of optimism in this space I think that's one of the reasons why.

Jay Kreps: So when I talk about just kind of, you know, overall a ton of optimism in the space, you know, I think that's one of the reasons why. Great, thanks, Millard. We'll take our next question from Mike Sickles with Needham, followed by Barclays. Great, thanks for taking the question here, guys. I know that you had spoken about the win rates versus CSPs and that being an area of doubling down for you. I guess one of the things that it seems like it's a bit of a shift in message here, given you guys have historically spoken about soaking up that Kafka opportunity. So to be going after the CSPs more directly, is that potentially a longer sales cycle? Because now you're going into an organization that has been ingrained in some capacity with an existing vendor.

Great. Thanks, Miller will take our next question from Mike <unk> with Needham followed by Barclays.

Great. Thanks for taking the question here guys I know that you had spoken about the win rates versus csp's that being an area of doubling down for you.

I guess one of the things it seems like it's a bit of a shift in message here. Given you guys have historically spoken about soaking up that kafka opportunity so to be going after the CSP more directly.

Is that is that potentially a longer sales cycle, because now youre going into an organization that has been ingrained in some capacity with an existing vendor.

Can you just kind of walk us through what are the mechanics been thus far that you've been able to evidence as far as those displacements you sided yeah.

Jay Kreps: And can you just kind of walk us through what are the mechanics been thus far that you've been able to evidence as far as those displacements you cited? Yeah, yeah, it's not a, you know, first of all, it's not exclusive. It's not like we're stepping back from the open source Kafka in any way. You know, I do think we probably pay less attention to these, you know, customers that had picked something from the cloud provider. It's actually not a longer sales cycle. In some sense, it's easier because there's less of a team that does the self-management that has to be displaced and accounted for. You know, you're basically swapping in a better product for less money.

Yes, it's not a yes.

Yes first of all it's not exclusive side, we're stepping back from though consensus Kafka anyway.

I do think we probably pay less attention to these.

Customers in and pick something from the cloud provider.

It's actually not a longer sales cycle and sometimes it's easier because there is less of a team that does the self management that has to be displaced and accounted for you basically swapping in a better product for less money and so yes. When we look at just kind of the overall sales staff against that one of the things that motivated us.

Jay Kreps: And so, yeah, when we look at just kind of the overall sales stats against that, one of the things that motivated us here was, you know, what we felt we'd done in the product portfolio. But part of it was just quantitative where we felt like, hey, you know, these deals are, you know, winning at a high rate and progressing quickly. And we know where it is. So it makes it easy to kind of package it up and teach the sales team to do that competition. Understood. And then just a quick follow-up for Rohan. I know, again, we're talking about the changes to the cloud consumption here. If I go back a quarter ago, you guys were already assuming that we would not see a return to what normal behavior would be on that sawtooth pattern. And it sounds like, again, we're adjusting our guide here.

Here was.

What we felt we've done in the product portfolio, but part of it was just quantitative where we felt like hey these.

These deals are.

Winning at a high rate and progressing quickly and we know where it is so it makes it easy to kind of package it up and teach them.

To do that competition.

Understood and then just a quick follow up for Rowan I know.

Again, we're talking about the changes to the cloud.

Consumption here, if I go back a quarter ago.

As we were already assuming that we would not see a return to what normal behavior would be on that so to pattern.

And it sounds like again <unk>.

Adjusting our guide here so did the consumption trends in Q2 actually deteriorate.

Jay Kreps: So did the consumption trends in Q2 actually deteriorate from where we were just in Q1? Can you provide some more granularity on that front? Yes, Mike. Yeah, so I'm an overall consumption Q1 to Q2. I would put it in the category that the true dynamics we called out were fairly consistent, that optimization of larger customers and slower use case adoption. So those two continued. If you look at month-over-month growth rates, they were flattered to slightly down from Q1 to Q2. And that's obviously driving us as we think about the second half to make sure that, you know, our assumptions around month-over-month growth rates are notably below what we've seen for the same period of prior years. So that's the dynamic on the cloud.

From where we were just in Q1 can you provide some more granularity on that front.

Yes, Mike from an overall consumption in Q1 to Q2 I would put it in the category that through dynamics, we called out for sale.

Fairly consistent that optimization of larger customer wants them slower use case.

Adoption. So those two continued if you look at month over month growth rates. They were flattish to slightly down from Q1 to Q2, and that's obviously driving across as we think about the second half to make sure that you know our assumptions around month over month growth rates are notably below what we've seen for the same period of prior years. So.

That's a dynamic on the cloud however.

I just wanted to.

Jay Kreps: However, you know, I just want to remind around the green shoots that we called out in the call in different parts of our prepared remarks. First, I mean, Jay spoke about the Flink and the momentum in Flink. And we 3X this year, we're closing in on the $10 million run rate. Second, we spoke about Warpstream. That business also showed really good growth in Q2. And the momentum is great. We spoke about the late-stage pipeline progression. And we also spoke about larger customers starting to commit more. So all of these are green shoots. So at balance, obviously, you know, the consumption is baked into it, into our guidance for the back half. But some of the green shoots are something that, you know, we're excited to make sure we execute on and, you know, go and beat this number that we have. Understood. Thank you.

Remind around green shoots that we called out in the call in different parts of our prepared remarks, Firstly, Jay spoke about the fleet and the momentum and demand planning and we <unk>. This year, we're closing in on the $10 million run rate.

We spoke about Gulfstream that business also showed really good growth in Q2 and the momentum is scraped.

We spoke about the late stage pipeline progression and we also spoke about larger customers starting to to make it more so all of these are reinsured. So a balance obviously you know the consumption is baked into it into our guidance for the back half, but some of the greenfields have something back.

Excited to make sure we execute on.

Go and beat those numbers that we have.

Understood. Thank you alright.

Alright, Thanks, Mike we'll take our next question from Raimo <unk> with Barclays followed by D. A Davidson.

Jay Kreps: All right, thanks, Mike. We'll take our next question from Raimo Lenshaw with Barclays, followed by D.A. Davison. Okay, perfect. Thank you. Thanks for squeezing me in. Rohan, if you talk about the two drivers for the situation we have on the cloud side, like how much of that is driven by just one customer, the one that you kind of mentioned for Q4? So is that the majority of what's going on, or are we talking several accounts here? No, what we said was, right now, like the larger customers broad base, like some of our larger customers, they are just optimizing and the slower use case adoption. If you look at guidance and what we spoke about, the primary, the driver for guidance is our assumption for month-over-month growth rates. So that's the primary driver.

Okay perfect. Thank you thanks for squeezing me in.

Everyone. If you talk about the the two drivers for the situation we have on the cloud side like how much of that is driven by just one customer that one that you guys have mentioned for Q4. So is that the majority of what's going on or are we talking several accounts here.

No what we said was right.

More like the larger customers broad based like pharma and some of our larger customers, they're just optimizing and the single use case adoption.

If you look at guidance and what we spoke about the primary driver of our guidance is our assumption for multiple months both right. So that's the primary driver the dynamic that we saw in the first half of the O&M in Q2, which is just the larger customers are optimizing for cost and slower use case adoption, that's probably one of the better you spoke about with.

Jay Kreps: The dynamic that we saw in the first half of the year and in Q2, which is just the larger customers optimizing for cost and slower use case adoption. That's the driver that we spoke about. With respect to the AI-native customer, that's just us providing some color commentary as we look at the back half of the year and how we think about some of the puts and takes for the cloud business. Yeah, okay. And then Jay, one for Jay. Jay, if you think about the optimization and what's going on there, is that people kind of doing more workloads in open source Kafka or like, because like if you think about the overall volume seem to be going higher. So how do you optimize there? Can you just remind us there? So yeah, it's not, you know, we would characterize movements to open source.

Respect to the AI native customer, that's just us providing some color commentary as we look at the back half of the yard and how we think about some of the puts and takes for the cloud business, Yes, Okay and then Jay.

T J, if you think about it.

Optimization and what's going on there is that.

People are kind of doing more workloads in open source kafka or like because like if you think about the overall volume seem to be going higher. So how do you optimize there can you just remind us or remind us.

So yeah, it's not we would characterize movements to open Srs, that's effectively churn right, it's not optimization.

Jay Kreps: Yeah, that's effectively churn, right? It's not optimization. You know, customers are moving off your product. Now, you know, what do we mean by optimization? You can try and take a lot of clusters that you have used across the company, combine them into bigger clusters and try and get some efficiency there. You can try and compress the data. You can try and optimize some of the usage patterns so it's more resource efficient. You can also do something more contractual where you kind of really model out your growth and commit to something bigger in return for a larger discount. Like all of those are the types of activities for customers that are, you know, looking to save. You know, it was the case entering this year. You know, last year had had a very heavy focus on consumption.

And moving onto your product the <unk>.

What do we mean by optimization you can try and take a lot of clusters that you have used to ask the company and combine them into bigger clusters and try and get some efficiency that you can try and compress the data you can try and optimize some of the usage patterns. So its more resource efficient.

You can also do something more contractual where you can't really model out your growth and commit to something bigger in return for a larger discount like all of those are the types of activities for customers that are.

Looking to save.

It was the case entering this year last year had a very heavy focus on consumption, we were probably riding a little bit lower in terms of the forward commitments of customers to their future growth. So one of the things that we have done over this year is kind of take up.

Jay Kreps: We were probably riding a little bit lower in terms of the forward commitments of customers to their future growth. So, you know, one of the things that we have done over this year is kind of take up that commit coverage similar to the forward growth. That's basically a good thing. Like you see it in the RPO growth, but it does, you know, mean a somewhat higher discount. You know, that's kind of the normal discount schedule is you commit to more, you get a slightly better deal. And so that, you know, that would contribute to that as well, which is more of a contractual rather than technical optimization. Yeah, okay, perfect. Thanks. Hey, thanks, Raimo. We'll take our final question today from Rudy Kessinger with D.A. Davison. Great, thanks, guys. Peter sort of asked it earlier.

Not commit coverage tomorrow the forward growth, that's basically like you'd see it in the RVO growth, but it does mean is somewhat higher discount that's kind of the normal discount schedule as you commit more you get a slightly better deal.

And so that that would contribute to that as well, which is more of a contractual rather than technical optimization.

Okay perfect. Thanks.

Hey, Thanks, Raimo, we'll take our final question today from Rudy Kessinger with da Davidson.

Thanks, guys, Peter sort of asked it earlier.

Brian close to 90% gross retention rate just to put the skepticism duress does that mean above or below 90%.

Jay Kreps: Rohan, close to 90% gross retention rate, just to put the skepticism to the rest. Does that mean above or below 90%? It was marginally below 90%. Very marginally below 90%. Got it. Okay. And then a lot of positive callouts on the DFC products, in particular Flink and some others. But, you know, with ease, with what you're kind of implying for the second half and kind of high teams implied cloud revenue growth, what is core streaming cloud revenue growth growing at? Because you can kind of back in and make some assumptions around Flink and some other products, and it would indicate it's growing, you know, a good chunk lower than the overall cloud revenue. So any color you can share on just what is the core streaming cloud revenue growing?

It was marginally below 90%, but marginally below 90%.

Got it Okay, and then a lot of positive callouts on the DSP products in particular flank and some others, but.

With ease with what the kind of implies the second half and kind of high teens and pipe cloud revenue growth.

What what is core streaming.

Revenue growth growing at because you can kind of back end and make some assumptions around flank and some other products in the indicators is growing.

A good chunk lower than the overall cloud revenue. So any color you can share on just what is the core streaming cloud revenue Brian Yeah. We you know we haven't broken it all out but it is true.

Jay Kreps: Yeah, we, you know, we haven't broken it all out, but, you know, it is true that, you know, the DSP portion of the business is outgrowing, you know, core streaming. I would look at that streaming growth rate as kind of a combination of additional use cases, you know, growth and then optimization. And, you know, it is the case that, you know, certainly for the last few quarters, we've had more of that type of optimization, especially for some of the larger accounts. You obviously don't see that on the DSP side where customers are building up new workloads. You know, there's not a big existing consumption base to go optimize. All right, thanks, Rudy. This concludes our earnings call. Thanks again for joining us. Have a good evening, everyone. Thanks, everyone. Thank you.

The DSP portion of the business is outgrowing core streaming.

I would look at that streaming growth rate is kind of a combination of <unk>.

Additional use cases growth and then optimization and it is the case it certainly for the last few quarters, we've had more of that type of optimization, especially for some of the larger accounts you. Obviously don't see that on the DSP side, where customers are building up new workloads.

Not a big existing consumption base to go optimize.

Alright. Thanks, Rudy This concludes our earnings call. Thanks, again for joining us have a video neighborhoods.

Thanks, everyone.

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