Hello, and welcome to the Elastic's Fourth Quarter Fiscal 2023 Earnings Results Conference Call. All participants will be in a listen-only mode. [Operator Instructions] After today's presentation, there will be an opportunity to ask questions. [Operator Instructions] Please note this event is being recorded. I would now like to turn the conference over to Nikolay Beliov, VP, Investor Relations. Please go ahead.

Thank you. Good afternoon, and thank you for joining us on today's conference call to discuss Elastic's fourth quarter and fiscal 2023 financial results. On the call, we have Ash Kulkarni, Chief Executive Officer; and Janesh Moorjani, Chief Financial Officer and Chief Operating Officer. Following their prepared remarks, we will take questions. Our press release was issued today after the close of market and is posted on our website. Slides, which supplement the call can also be found on the Elastic Investor Relations website, at ir.elastic.co. Our discussion will include forward-looking statements, which may include predictions, estimates, our expectations regarding the demand for our products and solutions and our future revenue and other information. These forward-looking statements are based on factors currently known to us, speak only as of the date of this call and are subject to risks and uncertainties that could cause actual results to differ materially. We disclaim any obligation to update or revise these forward-looking statements unless required by law. Please refer to the risks and uncertainties included in the press release that was issued earlier today included in the slides posted on our Investor Relations website and those more fully described in our filings with the Securities and Exchange Commission. We will also discuss certain non-GAAP financial measures. Disclosures regarding non-GAAP measures, including reconciliations with the most comparable GAAP measures can be found in the press release and slides. The webcast replay of this call will be available on our Company website under the Investor Relations link. Our first quarter fiscal 2024 quiet period begins at the close of business on Monday, July 17, 2023. On June 6, 2023, we will be participating in the Bank of America Global Technology Conference. And on June 7, 2023, we will be participating in the Rosenblatt Technology Summit. With that, I'll turn it over to Ash.

Thank you, Nikolay, and thank you all for joining us. I'm pleased with how we performed this quarter, given the global market environment, and I'm pleased with our results for the full fiscal year. We remain completely aligned to the needs of our customers, have prioritized focus areas for our business and continue to be confident about the opportunity ahead of us. Elastic has always had a singular mission, enabling everyone to find the answers that matter from all data in real time at scale. Generative AI and its chat-based intuitive approach to information systems, is opening up new opportunities for businesses to offer better services to their customers, make their processes more efficient and drive new insights from their data. Elastic has been investing in AI and ML capabilities for years, and we have many existing customers and use cases that demonstrate our successes in this area across search, observability and security. Our newer capabilities, including the Elasticsearch Relevance Engine or ESRE and vector search have enabled us to be a key component of the emerging AI stack to democratize generative AI and enable customers to optimize large language models with their own data in a secure way. We are very excited about the long-term opportunity this represents for Elastic. Now turning to our most recent quarter. In Q4, total revenue grew 19% year-over-year in constant currency with Elastic Cloud growing 30% year-over-year in constant currency and representing 40% of total revenue. We saw solid customer contractual commitments with customers continuing to consolidate onto our platform. We again managed the business with discipline to deliver a stronger-than-expected non-GAAP operating margin of 8.6%. For the full fiscal year, total revenue grew 24% year-over-year and 28% in constant currency, with Elastic Cloud growing 42% year-over-year and 44% in constant currency. We…

Thanks, Ash. We delivered solid results in the fourth quarter, finishing a good year for Elastic despite the current economic environment. We are pleased that we once again came in above the high-end of both our topline and bottom line guidance for the quarter. In Q4, we delivered 19% year-over-year constant currency growth in total revenue and Elastic Cloud grew 30% year-over-year in constant currency. Importantly, we delivered non-GAAP operating margin of 8.6% and are on track to achieve our goal of 10% for fiscal 2024. The overall trends we saw in the quarter remained consistent with the prior quarter. Customers want to do more with Elastic. There are three compelling reasons customers pick Elastic in the current business climate. First, our platform innovation to drive multiple use cases with any kind of data on a single stack. Second, a lower total cost of ownership and third, the flexibility of our consumption model. In addition, our many years of experience in AI and ML and the broad adoption of Elasticsearch for all sorts of search analytics use cases is enabling new conversations with our customers on generative AI. At the same time, we are helping customers optimize current consumption in the near-term. Being a reliable partner to our customers in challenging times increases our strategic importance to them for the long-term. As they bring more workloads onto the Elastic platform over time and as data volumes grow substantially, customers see greater business benefits, which in turn drives growth for us. This sets us up nicely for the long-term. Let's get into the results for Q4. Total revenue in the fourth quarter was $280 million, up 17% year-over-year or 19% in constant currency. Subscription revenue in the fourth quarter totaled $256 million, up 16% year-over-year or 18% in constant currency, comprising…

Thank you very much. We will now begin the question-and-answer session. [Operator Instructions] Today's first question comes from Matt Hedberg with RBC Capital Markets. Please go ahead.

Hey, Matt. Are you there?

Yes. Can you hear me okay?

Yes, we can. Go ahead please.

Sorry guys. Okay. Sorry about that, double muted. So yes, I wanted to dig into vector search and AI. To us, it seems like a large opportunity for you guys to see higher density models on the Elastic platform. Just kind of curious about what the early interest has been. Are you seeing any increased activity as it relates to vector?

Yes. Hey, Matt. This is Ash here. I can talk about this. So ever since we made the announcements of the Elasticsearch Relevance Engine literally, we've been having conversations with customers on a daily basis. Like it's – the interest has been just wonderful to see. And even with vector search, but it's when you think about generative AI, there are really two aspects to generative AI to build applications that are incredibly important. You can't do without either of these two components. So the first is the large language model itself. Whether it's GPT-4 or Bard or what have you. But these models are trained on publicly available data, and these models have no concept of businesses proprietary private data. And so if you are a business and you're trying to build a generative AI application, you really need to provide that private context to these large language models for it to be contextual to your business and your needs and for those answers to make sense in the context of the business. And that's really where Elasticsearch comes in. So the announcements that we've made, all the developments that we've done around vector search, in the last year and a half bringing that vector capability together with the textual search functionality, the BM25 functionality that we've had in the past, providing the hybrid search functionality and more importantly, doing it all on the same platform. So our customers don't need to purchase anything different and they don't have to get used to a new technology. They can just start to use the machine learning functionality and the vector functionality that's in the product with the same APIs, like this is a huge differentiator. And so from our perspective, we believe that we are uniquely positioned to be a winner in this space, especially when it comes to generative AI in the enterprise. So we're seeing that momentum in terms of customer conversations. We are very excited about what this opportunity represents in the long-term, how this translates into the expansion of the total addressable market. I think that we're going to get a sense of as we progress because there are lots of things that customers are working through. How do you do all these things in a way that your data privacy, your data security is handled in a good way, how do you think about model biases. So there's a lot of the stuff that you typically tend to see getting worked out in the early days of a new platform emerging. So that's what I expect we are seeing right now and what is happening. But in the long-term, I believe that this is going to be massive, and we are going to be in a really, really strong position to take advantage of this.

Maybe just a quick follow-up to that. Do you think when you start to see more of a monetization effort; is that one of the things that could start to inflect Elastic Cloud growth regardless of sort of broader macros? Like do you think that some of these trends are sort of stronger than sort of the depressed macros and you could start to see a rebound in Elastic Cloud growth maybe even sooner?

Yes. So when I think about the way in which we monetize vector search and all this AI functionality that we're talking about here, it's all in our premium additions, right? And the other thing is the machine learning capabilities tend to be pretty compute intensive. And as you know, both these factors tend to drive consumption for us. So obviously, as customers move from today, it's mostly individual consumers using something like a ChatGPT for all kinds of fun use cases and businesses are still trying to understand what are the kinds of use cases they want to build, what are the generative AI applications that they want to build for their own use cases, and we are at that stage. And as this turns into actual production, this is when we believe that it's going to really become very impactful and meaningful for us. It's still at this point where it's hard to predict how fast this will move, and we are appropriately just focusing on the execution right now and not thinking too much about when this turns into significant tailwinds for us. But in the long run, I'm very confident this is going to be significant.

Thanks guys.

The next question comes from Tyler Radke with Citi. Please go ahead.

Yes. Good afternoon. So Ash, another question for you on generative AI. I'm curious just as you look at the new customers that have come on to the Elastic platform I think you added about 300 this quarter, which was up from the 200 last quarter. Are you seeing any of these new kind of next-gen AI companies using the Elastic technology and using some of your new products that you announced? If you could just kind of talk about the composition of customers and maybe the use cases within kind of these next-gen generative AI companies where you're seeing your technology used?

Yes. So what we talked about even last week, when we announced at Microsoft Build, even there, we gave some customer examples, right? We talked about relativity, the customer that's using us for search use cases using us in conjunction – our vector search functionality in conjunction with large language models to deliver the kinds of use cases that they are looking to deliver for their customers. In my prepared remarks, I also talked about the large home improvement store in the U.S. that's looking to do something similar. They're working very closely with us. And these kinds of use cases, I believe, are not just going to be for the tech first kinds of organizations they're going to be for just about every business out there, right? So if you just think in terms of the home improvement customer that I mentioned, today, they use Elastic for all the product search on their platforms. So if you go on to their website and you search for miter saw or you search for a hammer, like it's Elastic that's figuring out what's the best product to actually like what's the most relevant product to show them. Now what they're interested in is effectively the kind of chat experience on their website which would be tremendously interactive and powerful. Like I'll give you an example. Like if a user comes to their website and says, I want to build an irrigation system for my two-acre backyard, what do I need? Now if you ask this question to ChatGPT, you're going to get very generic answers because ChatGPT has no idea what this particular store sells. And so the experience that this store – this company wants to deliver is effectively something along the lines for what you're trying to build based…

That's helpful. So Janesh, just on the cloud revenue here. So could you just talk about, did you see any incremental macro headwinds in the quarter? And then as you think about the guidance for FY2024, what are you assuming just to get to that second half acceleration that's implied? And then – and apologies if I missed it. Are you targeting a certain percentage of revenue is Elastic Cloud by year-end? Thank you.

Hey, Tyler. So overall, when I step back and just look at our performance in Q4, we were actually quite pleased. The quarter played out as we expected it would. There were many positives for us to highlight in the quarter. We touched on the number of customers earlier, the customers in the greater than $100,000 category. We generally saw from a macro standpoint – to answer your question, we generally saw the same trends that we saw in Q3. They continued into the fourth quarter. So we didn't see anything significantly different customers continue to engage with us. They are looking to bring more workloads on to the Elastic platform. They're looking to both do that to drive TCO savings but also just get greater business value. And at the same time, they are continuing to focus on ways in which they can optimize their consumption in the near term. And we're continuing to help them with that because our belief is that if we work closely with partners at this time, we emerge from this much more relevant to them. And as they bring more workloads on to Elastic, that actually helps us scale the business even better and faster over time. So that's what we saw. It was a consistent pattern. I'd say it was also consistent throughout the course of the quarter. It did not change in any meaningful way. And as I said earlier, it was sort of what we expected would happen. And also just a reminder for folks that Q4 is a bit of a shorter quarter than Q3, so that does have an effect on the sequential growth rate in Q4. And then looking ahead, as I mentioned earlier in the prepared remarks, we're excited about the momentum that we're enjoying with…

The next question comes from Koji Ikeda with Bank of America. Please go ahead.

Hey guys. Thanks so much for taking the questions. I wanted to ask another one on vector search. And thanks so much, Ash, on the use case examples. I think that's super helpful. And I just wanted to ask a couple of questions here on vector search. One, I think you mentioned that vector is only available on the premium edition. I just wanted to confirm that it's a paid feature only and there's no vector search in the open source or in the free version, question number one. And then number two, I totally hear you on Elastic being differentiated. I mean when I'm doing my checks out there, I hear that all the time from your user base, too. But could you help maybe explain it very simply on how Elastic's vector search is differentiated from the other vector search vendors out there?

Yes, great question. Koji respond to both of them in order. So in terms of the product features and the monetization, the vector searching functionality itself is in all editions, but the machine learning, how do you actually do the ingestion and creation of all of the vectors, all of that functionality, the ESRE model that we announced, the hybrid search capabilities that we announced, all of those are in the premium editions. So for all practical purposes, you need the premium editions to be able to build generative AI applications on our platform. So that's the monetization model. Now in terms of the differentiation, I can break it down for you in a few ways, right? So the first thing is, when you think about the emerging AI Stack, right, like I mentioned, there are two things that you're going to definitely need. The first is you're going to need an LLM, a large language model. And the second thing that you're going to need is some system that will allow you to provide the relevant context, and this is the most important piece because for every business, they don't want to ship all of their private data to the LLM. And more importantly, the LLM won't even be able to use everything because they are not built on having everything in real time, right? So your private data is constantly changing. It's moving in real-time. So the key is to provide for any given query from the – any interaction with the large language model, just a relevant context. And for this surface, you need at times the vector search functionality. At times, you need the textual search functionality and more recently, what people are discovering is you actually need a combination of the two in many, many different cases. And then for practical use cases, as you're building these applications, you need to be able to incorporate things like filtering, things like aggregation of these results. So for that reason, if you – if all you have is a vector database, you then need to still combine it with some technology like Elastic's to be able to bring all of this together, in our case, we've built everything in one consistent platform. The APIs are consistent with each other, and you can actually get – take advantage of all of these capabilities, including the ability to bring in external models directly from HuggingFace or any PyTorch model and run them on Elastic. So it's just a much more complete and much more capable solution than anything that's out there on the market. And that's the reason why we feel so confident about the unique opportunity that we have to be a real winner in the space of generative AI for enterprises.

Got it. Loud and clear, Ash. Thank you so much. And just one follow-up here for Janesh. Just thinking about the 2024 guide in cloud, it was just 40% of revenue in the fiscal fourth quarter. So for the guide, does that assume that, that mix of – that 40% mix, does it assume it goes up stay flat or go down throughout the year? Thanks guys.

Yes, Koji, great question. So we don't disaggregate the guide across the pieces. But overall, just given the momentum that we've had in cloud, given all of the product investments we are making, given the go-to-market focus that we've had, I would fully expect that cloud will grow significantly faster than the overall rate of growth in the business. So we should see a mix shift in cloud over the course of the year. We've just not quantified it, but we fully expect that, that will happen.

Got it. Thank you so much guys. Thank you so much.

Thank you. Looking forward to seeing you next week.

The next question comes from Pinjalim Bora with JPMorgan. Please go ahead.

Hey guys. Thanks for taking the question. Shockingly, another question on generative AI, ESRE. Ash, maybe help us understand for – obviously, Elasticsearch is known by developers. For somebody who has been working using and deploying, implementing Elasticsearch, how difficult would that be for them to now shift and deploy ESRE? Can that become kind of that familiarity with Elasticsearch, could that become an advantage for you guys as you kind of pivot towards this generative AI opportunity?

Yes. It's – Pinjalim, thank you for the question. It's a massive differentiator for us, right. If you think about the fact that Elasticsearch is the de facto platform when you think about search within the enterprise. And the way we have built the ESRE functionality, the relevance engine like it effectively brings together all of the vector functionality along with all of the BM25 textual search functionality, the hybrid capability to bring all of those to – these two things together. And it's all in a common platform with consistent APIs. And that last part about the consistent APIs is huge because that means that if you are familiar with Elasticsearch you now are naturally going to be able to take advantage of all of these capabilities easily. You don't have to learn completely new APIs. You don't have to figure out how to manage a new system and monitor it. Like effectively, what you have from Elastic, whether you have it in Elastic Cloud as an example, like you could just get started with this immediately. And like that's the reason why we feel very good about it. The conversations that we are having with customers is sort of reflecting this excitement. And like I said, the key is going to be seeing how this evolves and how businesses start to move these things into production. And I'm personally very excited about what this means for us in the future.

Got it. Very helpful. And one for Janesh. Janesh, the guide, when I'm looking at it, you talked about the sequential growth in Q4, the subscription sequential growth is basically flat. You're guiding to about 16%. It sounds like it's more of a second half story. Help us understand the kind of the confidence on that second half build from what you're saying, it sounds like there are some mechanics with the contracts that I guess we can't see. But obviously, you have a strong RPO. But I'm just trying to understand what gives you confidence for that to kind of reach that guide in the second half? And maybe help us understand the consumption trends so far in Q1 that you're seeing?

Yes. Pinjalim, as I think about the full-year, a couple of things, and I touched on this a little bit earlier, but I'll elaborate a bit further. So if you think about the way our contracts mechanically work, because we have either a one-year contract or we have – if we have multi-year contracts, you typically have annual breakpoints. And given the strength that we saw in contractual commitments that customers have made to us over the course of Q3 and Q4, and we were actually quite pleased with the outcome overall, even here in this quarter that we just wrapped up. As I look at all of those commitments, there are effectively natural mechanisms embedded in those contracts so that as customers consume against those contracts over the course of this year, we will see that translate to revenue. We're working actively with them for commitments that they've made to bring those workloads on to Elastic and to see that consumption ramp. But consumption can fluctuate from quarter-to-quarter depending on what actually happens with respect to that customer activity. So if the consumption ramps, that's great. But even if consumption trends stay similar to where they are in the first half, and that's the way we've built the model based on the Q1 guide, I'm just thinking about the first half overall, we will naturally start to see those contracts anniversary, and we'll then hit those breakpoints in the second half. So that gives us a good degree of visibility to ensure that there are certain amounts of revenue that will be recognized in fiscal 2024. So that's the mechanical aspects of the contracts. And that's why I was referring to the – if you looked at the short-term deferred revenue and you look at how much short-term deferred…

Got it. Thank you.

The next question comes from Ittai Kidron with Oppenheimer. Please go ahead.

Hey, guys. This is Harshil on for Ittai. I wanted to ask about the new AWS collaboration. What do you expect this to bring to Elastic in terms of dollars? Is there any color you can maybe give on how the integrated go-to-market activities will look? And then how is this different from how you bid with AWS up to now?

Hey, Harshil. Maybe I'll take that one. So as I think about the overall AWS relationship that we – and the contract that we just signed, it builds further on the partnership that we've enjoyed with AWS until now. Through these contracts, both parties are committed to significantly greater investments in areas like co-marketing, cloud adoption for workloads and so forth. The partnership itself covers a few broad areas. There's some of the integrated go-to-market activities that I mentioned, including marketing campaigns, guides, workshops and those kinds of activities. There are technology integrations. There are commercial incentives that we have embedded in them to drive the migration of on-premise workloads to Elastic Cloud on AWS. And then we're extending some of these practices globally as well. And within that, there's also additional work being performed for us to drive certain competency designations. You saw the security competency designation that we already announced. So it's a comprehensive partnership. It focuses on go-to-market. It focuses on the technology side in terms of additional reference architectures and better integrations. And some of these investments from both sides will happen over time, and they will bear fruit over time. But overall, when I step back and look at the evolution of the relationship and how far we've come, we've been really proud and pleased with the partnership and we look forward to providing you with further updates on the progress as we go.

Got it. Thank you.

The next question is from Shrenik Kothari with Baird. Please go ahead.

Hey. Thanks a lot. Congrats on the strong execution and the customer commitments. I was just wondering like how do you see the dynamic between – of course, we are hearing customers optimizing the consumption versus the strong commitments that you guys called out. Of course, there are all these prior innovations. You guys announced the relevance engine and the vector search, transform models and the ESQL as well, the feedback has been strong. So on your go-to-market and product strategies, I mean just curious if it involved more flexible kind of solutions, pricing terms, driving more value into existing packages. Just curious if you can unpack some of the go-to-market strategies there?

Yes. Hey. This is Ash here. Maybe I can take a crack at this. So this is what you're describing is sort of fundamental to our platform strategy, right? And what we are seeing right now in the market within our customers is everybody is being very cost conscious and towards that aim, they are looking to optimize their current workloads on Elastic, right. So as an example, we often will see customers moving more data to lower-cost object storage. And we often hear from customers that our frozen tier, which is where customers stored a lot of their data in low-cost offering storage tends to be faster than the hot tier of our largest competitor. And that's really pretty amazing. So we are able to save our customers not only the – in terms of total cost of ownership, but also deliver far greater value at a much lower cost. And that's one of the reasons why even as customers are optimizing their current workloads, they are making larger commitments to Elastic to be able to consolidate more onto our platform and move workloads that are currently on other competitor products on to Elastic. Now that takes a little bit of time to actually materialize in terms of moving those workloads over, but the commitments are really strong, and this is where, like I get very excited. The fact that we have amazing total cost of ownership, and I gave a very concrete example of this in my prepared remarks where the county in California was able to really get 3x the value. Effectively, these are the kinds of anecdotes that we are seeing. This is the kind of data that we are seeing. And we are really leaning into it. So we know that as more workloads come into our platform, eventually, that's going to translate into revenue, and that's really going to set us up very nicely for strong continued growth.

Got it. Thanks a lot, Ash. Appreciate it.

The next question comes from Blair Abernethy with Rosenblatt Securities. Please go ahead.

Thanks very much. Ash, just one more question, if I might, on the relevance engine. I guess I'm looking at this going very important and very powerful technology but I'm wondering, how are you looking at from a go-to-market standpoint, helping your customers to really get full leverage out of this? Is it through a step-up in professional services on your part? Is it through partnerships, training? And if you look back a few years, you guys built quite significant solutions around observability and security. Is there a similar kind of path here eventually?

Yes. So the best way to think about our go-to-market on this is, effectively, it's both a combination of the bottom-up motion that we've always driven really strongly with developers and the top-down motion that we drive through our go-to-market teams in the enterprise and commercial segments. So in terms of developers, like you're seeing a lot of blogging from us. You're seeing us be very involved in terms of the events that we are driving, like stand-ups and meet-ups and so on. And you're going to see more and more of that from us because right now, this is – in these early phases, it's the developer community that's really leaning in and stepping ahead to build new kinds of generative AI applications. And these developers are in every business, right, in every small and mid and large business. And they are the ones who are experimenting, who are playing with all of these capabilities. So we are making sure, first and foremost, that we are front and center with that community. We are leveraging the fact that Elasticsearch is so well known and really leaning into it. At the same time, our sales teams are going out there and making sure that all our large customers that they are using us for either search or observability or security, understand this new capability and what it can mean for them. We are having sessions where we're doing brainstorming with our customers on, hey, what are the kinds of opportunities within your enterprise that this could unlock for you. And so it's going to be both in the bottom up and the top down. But what we will continue to build on top of is an amazing brand that Elasticsearch has out there in terms of search.

Great. Thank you.

The next question comes from Raimo Lenschow with Barclays. Please go ahead.

Thank you for squeezing me in. We talked a lot about AI, but it's kind of probably more the future. If I think talk more about the current situation, can you see a little bit what you're seeing in terms of the optimization journeys we see with your clients? Where are we on that? It's obviously a question that comes up for the hyperscalers, it does impact you a little bit as well. Can you kind of talk a little bit of what you're seeing there in terms of where customers are in kind of identifying where they could spend less at Elastic and pushing it through versus like most of that is done from now on, people are as efficient as they can tend to start spending more with you? Is there any update there?

Yes, Raimo. This is Ash here. Maybe I'll lead off and then Janesh may want to add to it. But in terms of the most common kind of optimization that we are seeing customers doing with the existing workloads is moving more and more data to object storage, right, to our frozen tier. Like that's one of the most common practices. And frankly, like we are leaning into that and helping them because like I mentioned, we are – the feedback that we are getting is that our frozen tier is actually faster than the hot tier of some of our most common competitors. And so that's a huge advantage. Now the reality is that there's only so much that you can move to the frozen tier and also when it comes to the fact that data itself is continuing to grow, like there are natural limits to what you can do in terms of optimization. The fundamental question that you're asking in terms of where are we on this journey? Like what – we're not seeing any increased pressures, right. So like Janesh mentioned, where we are today is roughly like what we saw in the last quarter as well. But the data volume, the fact that data volumes are continuing to grow and the fact that newer workloads are coming on to our platform as customers consolidate onto our platform just means that that's going to be the offset in the coming year and beyond. And that's what we're just leaning into because it also allows us to take market share. So when people become more comfortable in terms of their spending patterns, like that's just going to be – by that time, we are going to be in such a better position in terms of market share that it's really going to set us up very nicely for the future.

Yes. Okay. Perfect. Thank you.

Next question comes from Brent Thill with Jefferies. Please go ahead.

Janesh, you mentioned the May sales kickoff. When you go into this next fiscal year, are there any major changes or tweaks you're making on the go-to-market? Or is it pretty much following the same playbook that you followed last fiscal year?

Hey, Brent. The go-to-market model fundamentally for us will largely continue to be the same. If I think about the structures that we've had and the model that we've put in place, it's working quite nicely. We are continuing to focus on building commercial and enterprise sales coverage. We've also had success with our focus on cloud, and we see that in the strong commitments and the sales force is effectively much more focused on selling cloud. We are increasing our focus on consumption as well a little bit. And starting this fiscal year, we've actually included a small consumption piece to the sales compensation plan as well. I think that will help overall as we think about scaling the cloud business in the future. And if I think about the other elements of our go-to-market around our partnerships with the hyperscalers and the marketplaces, those are all working very nicely for us as well. As you saw with the announcements from – with AWS, we're putting a lot of energy into this area. So we feel good about our overall go-to-market structure, but looking forward to executing here in Q1 and the rest of the year.

And real quickly for Ash, just on the AI solutions. When do you expect the kind of stand-alone monetizable solutions on top of the platform will be able to be monetized. I know maybe you can't give an exact GA date. But is that front half of the fiscal year, back half of the fiscal year? How do you think about the timing?

Yes. In terms of the actual features, like they are available now. So it's not about GA, it's more about customers themselves building these applications and putting them into production, right? So it's less about us delivering any functionality. We've delivered the core platform, right? The ESRE announcement was like the key announcement there. Now we are also building our own co-pilots, right, for observability and security all built on top of that same ESRE functionality, and those will be coming very shortly. But fundamentally, the platform for building generative AI applications are there today. And it's more about customers sort of moving from where they are today, where they are trialing things, they're playing around with things to getting to the point where they put things into production. And as that happens, that's – in my opinion, that's going to follow some of the natural curves that we've seen in the past where you've seen like major technology platforms emerging but when the pendulum swings it swings in a very big way. So I can't quite predict the timing, but feel very good about both what this represents in the long-term for us and our ability to be a winner in this space.

Thank you.

The last question comes from Rob Owens with Piper Sandler. Please go ahead.

Hi. Thanks for taking my question. This is Ethan on for Rob. Janesh, I wanted to ask around the 100,000 plus customer base. It seems like consistent net adds here again in the quarter, but I wanted to ask around kind of revenue growth from this cohort for the year, whether that's in terms of NRR relative to the rest of the base or kind of what the revenue mix was from these customers for the year relative to recent years? Any color you'd be able to provide on that would be helpful? Thank you.

Yes. Happy to talk about that a little bit. We don't discretely break out the size in terms of dollars or the revenue from the space on a quarterly basis. But what I can tell you is that larger customers are increasingly focused on to consolidation. They see the benefits of the platform that we've talked about. They see the benefits of the consumption model. So when you think about our core land-and-expand motion, that continues to work quite nicely. Most of these customers that we added in this category started off as less than 100,000 and then eventually grew into the 100,000 plus category. And then the sales team, of course, also did well to close a number of meaningful deals in the quarter. So it's a part of the business that is a good indication of expansion. It's a good indication of our progress in the enterprise and the commercial side. And we expect that we will continue to drive that motion going forward.

This concludes our question-and-answer session. I would now like to turn the call back to Ash Kulkarni for any closing remarks.

Thank you all for joining us today. Like I mentioned, we remain confident in our ability to drive both growth and profitability as we've demonstrated and are excited about our unique position in generative AI. We look forward to updating you on our progress as we go. Have a great evening.

The conference has now concluded. Thank you for attending today's presentation. You may now disconnect.