Thanks for joining us for our next session. I'm really happy to have the team from Confluent here. I'll start with you, Rohan. A lot of things happened, you know, since you reported the Q3 results, and just to kind of ground everyone, just kind of maybe talk a little bit about, like, what you've been seeing out there, you know, like Q3 and since, you know, weaving in that classic hedge fund question of post-election, how things are playing out, etc. Like, maybe, yeah, maybe we start with that one, yeah. We'll be happy to, Raimo, good to see you, and thanks for hosting us. Yeah. Our Q3 results were something that we were very pleased with. When you look at the headline numbers for Q3, we grew our total business subscription revenue at 27% year over year on the heels of our Confluent Cloud performance of 42%. When you take a step back, that's at a $500 million run rate, so high growth at scale. We did that while growing our operating margins and free cash flow margins north of 10 percentage points. Headline numbers we were pleased with. What are the puts and takes for the quarter? You know, I mentioned that one area of focus for us over the last 12 months was the digital native segment. We did see stabilization in the digital native segment from a consumption standpoint in Q3. That was on the heels of stabilization coupled with some of our larger digital native customers starting to look at net new use cases and adopt our DSP. That was data point number two. Data point number three, what I'll say is, since the beginning of the year, we've been talking about our data streaming platform. What we've done over the first nine months from a data streaming platform perspective is we've had a series of technology innovations, be it GA of Flink, be it private networking for some of our other products. That has continued through the year. We are pleased with the momentum of the technology innovations that we've kind of put out there in the market. Mm-hmm. And our focus in the first nine months has been around adoption. And I'm sure Erica will touch on it. It's also building that muscle to sell a multi-product platform. And that's been the focus. And over the first nine months, we are pleased with the progress that we've made. A lot of wood to chop, but we feel good with where we are in the first three quarters. Mm-hmm. To your other question, I don't want to break new ground in this meeting around in-quarter progress. Yeah. Right? But hopefully that helps set the stage. Not to talk about your numbers, Erica, but like, when you go to the clients and talk about with customers about it, like, how does it feel out there in terms of, you know, excitement, kind of better? Like, how, you know, what's the mood out there from a customer perspective when you have conversations? Yeah. Happy to share that and thank you for having us here. I had a lot of customer meetings last week at AWS re:Invent, for example, meeting with a lot of the executives at customers and prospects and key partners. Yeah. I'd say that, you know, first and foremost, there's a lot of enthusiasm for and kind of acknowledgement that real-time data streaming is becoming more and more core. We're having bigger conversations, which is really exciting. Yeah. We're talking to CTOs and global SIs about the transformational power and the unlocks of leveraging real-time data streaming and the value of a complete data streaming platform. I think that's becoming well understood. Yeah. We talk to our customers about the benefits of a technology strategy or a, you know, data architecture where we shift left and shift the governance, the processing, you know, the connections between different sources and sinks of data. We shift that left in the environment so that our customers can produce data products that can be reusable across the operational state and the analytical estate. Mm-hmm. And that's a message that's really resonating, and it's a strategic message and something that CTOs want to partner with us on, and so I think that's, that's the difference, you know, over the last year plus is that this is just becoming much more transformational and core, and we're super excited about that. Rohan, back to you. You know, you did mention the digital natives already a little bit, like, in terms of, like, more stabilization. Like, can you talk a little bit more, bigger picture about them? Like, you know, how important are they for you? Like, what's the, like, how are they thinking about it, and how are you fitting in there? Yeah. I get this question all the time. All right, what do you mean by digital native? Yeah, yeah, exactly. Right? Yeah. I didn't want to ask it that simply, but, like, yes, yeah. Yeah, but the digital natives is essentially you can think about customers who are technology forward, leaning towards the latest technology, and you know, as you can think that those are the customers that are going to be adopting real-time data, so let's do, like, three lenses. Let's go back. Let's talk about Q3, and then I'll talk about, like, going forward. Mm-hmm. If I look at the last 18-24 months, this digital native segment for us has been a growth driver. But you've heard us talk about it, that, has the growth always been linear? Probably not. We've seen a little bit of a sawtooth pattern. Mm-hmm. Which is not surprising. But when you take it over a period of time, it's been a growth driver for us. Q3, we said that the broader digital native segment, we did see stabilization in the consumption. And primarily, we also started seeing some of our customers adopt new use cases. So that was Q3. And looking ahead from my perspective, digital natives is a segment that we are under-penetrated, and it is going to be a growth driver for us. Mm-hmm. Oh, I also, if I take a step back, I also like to provide a little bit of the timeline. You know, when, Raimo, when you look at Kafka as a technology, that's about 13 years old, 13, maybe 14. Confluent, we are about a decade old. And our cloud-native product that we are selling at scale is a little over six years old. So, and our DSP, we're 2024 is the year of the DSP for us. Mm-hmm. So as you think about the technology innovations and how we can actually make a difference for our digital native customers, not only from a technology perspective, but also from an ROI, TCO perspective, we're continuing to make progress in the right direction. So that's, that's how I'd frame the opportunity. Yeah. Okay. And then the Erica one for you. Obviously, like, in your conversations last week, I'm sure Gen AI came up a lot. How do you think, you know, Confluent will fit in there? And how is customer appreciation about, like, the role that you're going to play there? Yeah. It is a topic in so many conversations. Oh, absolutely. And not surprisingly, and in the simplest terms, Confluent can help move data from different, you know, company proprietary data from different silos around the company. Yeah. Into inference models. And so we can help complement, you know, public LLMs with real-time contextual, you know, company proprietary data. And that's a lot of value to companies. And of course, so many companies are in very early stages of figuring out what is the, you know, the highest value Gen AI play for them. But the focus on that prompts a focus on overall data strategy. Mm-hmm. That's really where we come in. It, it is definitely a topic in so many conversations. So if you think about, like, sorry, I'm trying to sound technical, but it probably not won't work. But if you think, like, the idea is I have my data set, but then I need kind of prompts coming in, using RAG to kind of do the prompts. So are you guys kind of, in a way, are you going to feed, make sure that this is because having real-time, especially if I'm an agent somewhere and trying to do have conversations, I need to have real-time. Yeah. Kind of answers there, yeah. Exactly. That's a great use case. I mean, we're seeing a number of customers adopt kind of the agentic, you know, types of use cases. And if you think about, you have an agent on the phone and maybe a customer service capacity, you know, one of our customers in the insurance industry. Yeah. You know, we're, we're feeding real-time information about what may have just transpired with that customer. So the agent has real-time data available. Yeah. yeah. Where are, like, so that's one example. Are there more examples like that, or, and where are customers in understanding that? It's like they just, because, like, we just had Databricks earlier, and they're like, "Well, we need to get the data into the right places for us. Yeah. That's another thing. Where are we on that kind of customer understanding journey? I think we're early. I mean, I think in our traditional companies, we are seeing, you know, examples like I just described. We also are seeing examples of leveraging, real-time data to assist doctors, you know, facing off to patients with, you know, more real-time information and contextual information. So there's a lot of those sort of, agentic and, you know, interaction type, Mm-hmm. examples that we're seeing, you know, great traction with. And then also, we're very focused on partnering with AI companies. And so we're fortunate to call OpenAI a significant customer, Notion a significant customer. And so we're working with them to be just core, you know, data underpinning for what they offer to the market. So we're kind of coming at the Gen AI opportunity from a couple of different angles. How do you think, obviously, like, if I'm looking at Marc Maurer's data footprint, it's a, excuse my language, Marc, it's a mess, you know? Like we said, so many different places. Like, how do you think about the speed of adoption here? I think, you know, again, the conversation that we're having with customers is really about looking at the overall architecture and finding the opportunities to, you know, if you think about that data mess. Mm-hmm. Kind of organize it into, you know, by shifting left, how can we earlier in the process, you know, govern the data, have data lineage available, you know, process the data so that you're creating these valuable data products. Yeah. With awareness of, like, what are the different operational and analytical systems that they will feed? Because a lot of what creates the data mess is you're streaming data over into, you know, one application or one data lake or data warehouse, but then you're manipulating the data there, and you're not able to reuse it, somewhere else. And so if we can shift left and do that work earlier in the process, it helps kind of tame the mess. Yeah, yeah, yeah. Yeah. Then Rohan, for you then, like, is that showing up, or what are you seeing in terms of the conversation? Is that showing up more on cloud or more on-premises or both? Or how do you think about that? I mean, early days, feel free to chime in, Erica. Yeah. Early, early days for us, but as we are looking at the pipeline, cloud definitely seems to be benefiting from a pipeline perspective. But I'll, I'll call out that, yes, we are seeing early traction in cloud, but you've heard me talk about it, that we need to be wherever our customers' data and infrastructure lie. So for some of the inference use cases, if the closest data point is on-prem, we'll probably see benefit from on-prem as well. So all I'm saying is early traction is on the cloud side, but we expect our entire portfolio to benefit as we look ahead from Gen AI. Mm-hmm. Yeah, that's right. I think it's been actually, well, first off, our, you know, the Confluent Platform business continues to thrive, particularly in regulated markets. Yeah. But also in traditional companies where, as Rohan points out, there's still, you know, data stores in, you know, data centers and on-premise environments. And so our ability to meet customers where they are, whether the data is on-premise or in public cloud and across multiple public clouds, has been a real advantage for us. Yeah. And then, I want to shift gear a little bit, like, WarpStream. How do after, like, obviously, WarpStream standalone had kind of was very vocal about, like, where they think the world is going and where they fit in. You know, you communicated where you see them. Like, how do, how is this playing out for you guys? I'm happy to speak to that. Yeah. I'll chime in a second. Go ahead. Oh, yeah, sorry. Yeah, yeah. Yeah. So for WarpStream, a big part of our strategy, our mission is to soak up the world's Kafka, and we have over 150,000 organizations using open-source Kafka. And when you really think about how this mission will come to fruition, it's more around, it's less about the customers, more about the individual use cases, applications that these customers are running. Mm-hmm. For each of these applications, we want to have a solution which has the right amount of ROI and is meeting the needs that the customer is trying to solve. Historically, we've been on-prem, we've been on the cloud, we're trying to meet the customer where they are. We started to see this category emerge where you're bringing your own cloud. That is, you're using your customer's infrastructure to provide them with a solution, and you're not being super invasive with it. WarpStream basically fits in with that in mind. WarpStream essentially is a bring your own cloud product where if you have really large data that you're moving, large amounts of data, think logging, think observability, think data that you're moving to data lakes or data warehouses, right? Those are the use case. Typically, these use cases are not as latency sensitive as, say, a fraud detection. So with WarpStream, we can provide our customers with the right ROI. Mm-hmm. And also solve their use cases. So the way I think about it, like wearing the commercial hat on, is, it does a really good thing about expanding our serviceable, addressable market, and whereby it gets us, SAM, much closer to the TAM. So. Yeah. Do you want to add anything, Erica? I think that's right. And I think we're seeing opportunities. You know, where does that serviceable, addressable market show up? Sometimes it's in, you know, new logos that are kind of a great fit for the bring your own cloud offering for a more upstream. Sometimes it's specific use cases within existing customers where that addressable market might not have been as available to us until we have this offering. So the backdrop is, as Rohan says, we want to soak up all the world's Kafka, 150,000 organizations out there using Kafka. And the best way to do that is for us to have a portfolio of offerings. Yeah. To, you know, serve the needs of different customers and different use cases and workloads within those customers. Good. Yeah, so in a way, like, I mean, I had an industry guy describe it once. You're going to be like the real-time platform, but they say it basically means different aspects that you need to solve. Yeah. Yeah. And I mean, is that like a big part of the market potentially? Or like, how do you think about, I mean, you know, obviously you bought it, so it must have been exciting enough. But like, how do you think about that opportunity in comparison to the others? We're excited about the opportunity. When we think about, if you look at the acquisitions that we've made, be it Immerok, be it WarpStream, two things are common. One is best-in-class technology, and the second is really high-quality teams. WarpStream checks the box on that. Mm-hmm. So obviously, as Erica mentioned, it provides us with an opportunity whereby we're kind of expanding our service area for more of these use cases to come to Confluent. And we expect this to be, you know, a fairly big opportunity over the long term, but you know, it's a product that's a year old. And our focus at this point is hardening the product. It is, we are selling it, but hardening the product. And you know, that'll be the focus as we head into next year. So then if it's a year old, it's tiny. Sorry, from the, like, I'm the revenue guy, yeah. So it's still tiny as a, as a product in a way. For Q3, I did mention that for Q3, both from a revenue and an expense perspective, it was not material to our financials. Yeah, yeah, yeah. But in accounting terms, not material? Well, let me put it. It was de minimis. Yeah. Right? Okay. Okay. Good. Okay. Perfect. And then, the other big product where we are a little bit further down the line is Flink. Can you talk a little bit about, you know, we start with Erica maybe, like, from a customer perspective, like, you know, I went to your conference like a year or two ago, like Flink was kind of mentioned a lot because it's like, it's very difficult to do and people wanted handholding. So you finally have it now. Like, what's been the customer reaction since you launched it on the cloud? We continue to see a lot of enthusiasm and excitement for Flink and really robust, you know, what we might call top-of-the-funnel activity. Mm-hmm. And then we're partnering with customers to make sure, because it is hard to make to partner with them to get them into production. So I think we've kind of thought of 2024 as the year of adoption of getting, you know, customers into the cycle with us around Flink, you know, with further opportunity, monetization opportunity into 2025. But so far, you know, a couple highlights that, you know, we'd call out in terms of customers leveraging Flink and, you know, what are they doing with it. We have a major grocery retail chain, who's leveraging Flink for real-time. Yeah. Dynamic pricing and promotions, you know, different in different markets. A Fortune 50 telecommunications company is leveraging Flink pretty significantly. So we're excited about the kind of early indicators of the, you know, the value of the use cases. How do I think about when you say adoption? So is this year in a way like the old classic software? I would say like the reference customers to kind of adopt them, and then you can go out and show, like, look, here's the retailer, here's the telco, and then you just broaden it like next year, then the broadening or like is that the way to think about it? I think that's a good way to think about it. Yeah. You know, because it is a hard category, we want to make sure that we have the reference architectures and the right resources for company, for customers so that we can. Yeah. Help them at scale, or, you know, get to the market at scale. So that's what part of the benefit of. And do you need to, or is that kind of how much handholding do clients need from a, like, a services organization? Is there a lot that is still need, that is then needed? And is it like an SI opportunity? How do you think about that? It is an SI opportunity. We have a couple of partners who have really focused and built up specific expertise in this area. So they've been instrumental. Yeah. In going to market with us. We see it as a great SI opportunity. Yeah. And then Rohan, like, number question, the, like, how do I think about like Flink then on the number side? Like, I don't know, like, and I should probably remember the, how much you kind of talked about it in the previous quarters or want to talk about. Yeah, you know, before I get into the numbers, Erica made a point earlier that I want to underscore around Flink governance, the data streaming platform. One thing that's resonating with us, we're resonating with some of our tech execs for our customers is essentially moving processing and governance earlier in the lifecycle of data. Mm-hmm. As this data moves to the destinations, it is in a place where it's usable. When you really think about the Flink opportunity, that's how we think about it, right? It is making sure that we are moving higher quality data into different parts of the organization. Beginning of the year, we shared some high-level metrics on DSP. We said that DSP is approximately 10% of our cloud business. When you break that down, it's primarily the connectors followed by governance, and Flink was just launched at this point. Mm-hmm. So that was a mix. Without getting into numbers, looking ahead, when you ask, if you ask me where's the largest opportunity, at least where we stand today, where we feel is the largest opportunity, we feel Flink has the largest opportunity followed by connectors, followed by governance. Mm-hmm. So if you think about it, where it is mathematically, you know, you're in the earlier stages of the S-curve for each of these products. In general, these products are growing faster than the average revenue. Okay. Right? And, as we look ahead over the next couple of years, it's going to be a growth driver for us. So, that's how I think about it. Can I buy Flink as a standalone or is Flink always part of the DSP offering? If you can buy standalone, but obviously the value of it is as part of the broader portfolio. Yeah. Would that be? Is it cloud? Well, it's cloud. Can I do? Is it all in cloud or can I do Flink also kind of on the platform side? Yeah. I think Erica briefly touched on it. It is primarily on the cloud. Yeah. The philosophy, the tenets with respect to how we've built this product is very similar to our broad Confluent Cloud product, which is it's cloud native, it's complete, and it's available in all clouds. Mm-hmm. So that's how it is. But we also have an on-prem version of Flink, Flink for CP. Mm-hmm. Which, the telecommunications company that Erica was talking about was Flink on CP. Okay. Okay. Makes sense. And then I wanted to switch gears the last few minutes. Erica, like we had like go-to-market changes. Mm-hmm. And you wanted to focus, SaaS cash more on consumption. Mm-hmm. Full disclosure, I had Mongo in yesterday and that was like a big topic of conversations, like how do you sell consumption successfully? And they had like a little bit of a wrong start because the sales catch, a good sales catch, they were selling consumption, but like not expandable consumption. Mm-hmm. And so then at renewal point, you have like a problem. Like you were a little bit later, so obviously you have a little bit of learning from those guys. Yeah. How is that playing out for you? Like, what was it the same idea and, you know, what were the guardrails you put in there to kind of prevent it? Yeah. Many of the same ideas, and then as you point out, we've had the benefit of learning from some of our peers in the market. We're all in touch and. Yeah. You know, what were lessons learned? What would you do differently? So, so that's been really helpful to us. And, you know, it's been, as, as you pointed out, we took on some change at the beginning of this year. We're nine months in, more than nine months in, and we feel like the significant change is behind us. You're always fine-tuning and adjusting, but the change going into 2025 is less than we took on in 2024. And the proof points of the consumption transformation, and maybe if I just take a step back to remind us, why did we do it? Mm-hmm. It really aligns the customer's like moment of value, which is get an application into production, and realizing value. It aligns our incentives and our motions with that. Our revenue model for cloud was already aligned with that. Yeah. We already were recognizing cloud revenue, not by subscription commitments or bookings, but by actual consumption. And so we aligned the sales motion and incentive structure to that as well. And we think there's been great benefit, great payoff. You know, one proof point is we look at our total customer count, but really how are we progressing customers to 100K plus spenders and million plus spenders? Yeah. The 100K plus customers, you know, account for 85% of our revenue base. And so we see that as a positive. We've seen consistent growth into those cohorts. And to your point, you know, you have to make sure you have the right guardrails upfront to acquire the right customers so that they grow. Yeah. Through those tiers. Volume at, you know, the front end without the propensity to grow is not as valuable to us. Yeah. Yeah, yeah. So we've been watching that. Yeah. The final thing I'll say is that, we also felt that the consumption transformation, in addition to just being the right thing in terms of aligning our incentives with the customer's moment of value, it's the right foundation for now moving from product to platform. Mm-hmm. Because as we, you know, now with our focus being on, driving adoption of multiple products in our customer base, we want that motion to be as low friction as possible for the customer and for the sales team. So now you can adopt, you know, the next product, you can just kind of turn it on and start using it in your existing environment. There's no contracting process or pricing negotiation before you do that. Yeah, yeah. So we can just move right into consumption and kind of disconnect it from, you know, renewing the contract. There's another product that needs to sign for. Yeah. Yeah, yeah, yeah. Yeah. So it's serving us now in our, you know, current model, and we think it's the right foundation as we go from product to platform. That kind of leads into my next question. In theory, that should make upsell cross-sell more easy to kind of achieve. But then we're the numbers guy, so we're looking at results. Like, speak a little bit to the NRR, like the 117% is healthy for the industry, especially at this point of the cycle, but it still came down a little bit. How do you have to think about that number versus kind of actually you're selling a much broader kind of product set? Yeah. For NRR, at least the lens I look at NRR is two things. Mm-hmm. I think to your point around expansion, that's one lens. But the first lens I look at it is, what's my GRR? What's the health of my install base? And our GRR has been north of 90% consistently, you know, over the last few quarters or over a while. So we feel good with the health of our install base. That's one data point. Second data point around expansion. In our Q3 call, we mentioned that we did see stabilization from the digital native segment, and as a result, we are expecting stabilization around the current levels is what I said at our Q3 call. Mm-hmm. However, if you kind of ask me, all right, long term, what are the puts and takes? The long term, the puts and takes are, it goes back to DSP, where our ability to sell DSP into our existing customer base is going to benefit to NRR over the long term. And, so that kind of drives with the broader narrative that we've spoken about for DSP. Mm-hmm. So that's how I think about it. GRR and from an expansion standpoint, DSP. Okay. Perfect. Yeah. So, and it's a lagging indicator anyway. Yeah. Yeah. Right. Yeah. And then, last question for me, and then I kind of need to let you go. So, operating profit levels have like improved quite a bit. Can you speak a little bit about like what you did to achieve it? And because like the question, like now that we're gonna back growth focus is like did we cut off growth or what's the implications on the growth side from the, from the changes there? Can you speak to that, Rohan? Yeah. As a company, ever since, in fact, even before we were public, there was this focus around our philosophy around resource allocation has always been growth and profitability. It's neither, it's not either or, it's and. And how I think about it is, as you're reallocating resources, how do you make, how are you driving durable growth and how are you doing it efficiently? So that's our resource allocation philosophy. You're right. Over the last few years, we've improved our margins north of 40 points. And, you know, that's something that can only happen if it's, in the DNA of the company. I mean, we're really, very focused on ROI-based investment. But at the same time, we're making sure that we are putting in the long-term bet that we need to put in. 2024 is a classic example with the product innovation that we've come out with. These are investments that we put in years back, and as part of your resource allocation philosophy, I think you need to balance it out. Mm-hmm. That's not gonna change as we look ahead. Is there how do you think about it if you are potentially, and Erica is going to listen very closely now? Like if we are improving on the economy, like you probably want more sales resources. How do you think about that, you know, getting ready? Because on the sales side, you need to hire nine, 12 months ahead. And so, you know, there is probably if you wanna take advantage of it, you need to do some more stuff. Yeah. I think I kind of attribute that to philosophy around continuous planning. You know, you do have knobs that you can move to the right or left. Jay, Erica, myself, we are very close with respect to how we think about that. You're making those investment decisions as you see things play out. So moving the knob to right or left, I think that's in our control and that, you know, we're constantly. It's a continuous process. It's not an annual or a biannual process. Yeah. I mean, where are you on sales productivity at the moment? Like, are you happy with, like, what's your headcount buffer? How do you think about that? Yeah. We're pleased with where we are. You know, we're and then also, as you say, like we always have an eye toward, okay, how do we continue to get more efficient but also have the right capacity. Yeah. That we need for future years' growth, and fund that in a year when the payoff, you know, might not be until the following year, and continue to improve productivity. So we're pleased with where we are. And as Rohan mentioned, we're in constant dialogue about when's the right time to sort of turn the knob, particularly with the DSP opportunity. And as we look out at different markets, different markets will be ready for, you know, to. Yeah. Take on more capacity sooner versus later. So we're in constant dialogue on that. Perfect. Yeah. Hey, it's a good closing statement as well. I think our time is up. Hey, I've really enjoyed our conversation. Thank you. Thank you. Thank you for having us. Thank you.