Good afternoon, and welcome to the Elastic Second Quarter Fiscal 2024 Earnings Results Conference Call. Please note, this event is being recorded. I would now like to turn the conference over to Anthony Luscri, Vice President, Investor Relations. Please go ahead.

Thank you. Good afternoon, and thank you for joining us on today's conference call to discuss Elastic's second quarter fiscal 2024 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 are supplemental to 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 or 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 risk 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 we issued earlier today included in the slides posted on the 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 third quarter fiscal 2024 quiet period begins at the close of business on Wednesday, January 17, 2024. On December 7, 2023, we will be participating in the Barclays Global Technology Conference. With that, I'll turn it over to Ash.

Thank you, Anthony, and welcome back to Elastic, and thank you all for joining us today. I'm pleased with how we performed in the second quarter, which is still a challenging external environment. We exceeded our expectations across both revenue and non-GAAP operating margin. In Q2, revenue grew 17% year-over-year with Elastic Cloud growing 31% year-over-year, fueled by continued improvement in cloud consumption as well as our success in generative AI. And we exceeded our profitability goal, delivering a non-GAAP operating margin of 13%. Elastic's mission is to enable everyone to find the answers that matter from all data in real time at scale. Search is at the core of all our solutions and everything we do, whether you are searching a website or searching for security threats in your organization. Search is also a critical part of the infrastructure for AI. We are proud that Elastic is the leading search analytics platform used by tens of thousands of customers and supported by a large community of users. Our thoughtful investment and innovation in AI has continued to drive customer excitement and engagement with Elastic, and this was visible in our business in Q2. During the quarter, we continued to see recurring trends drive momentum in our business. The first of these being generative AI. I met with dozens of customers across all geographies, and a recurring theme was a strong desire to use Elasticsearch Relevance Engine, or ESRE, to build generative AI applications. Generative AI is driving a resurgence of interest in search as customers use semantic search, vector search, and hybrid search to ground large language models with their private business context, and ESRE provides the most comprehensive and enterprise-ready platform for these use cases. While it will take some time for generative AI spend to become a significant driver of our revenue, we are very excited about the long-term opportunity. As an example, we signed a multiyear marketplace deal with DocuSign, the world leader in eSignature and contract lifecycle management solutions. More than 1.4 million customers and more than 1 billion users in over 180 countries use DocuSign solutions to make doing business smarter, easier, and more secure. Search is an essential component of DocuSign's product, and our advanced capabilities with semantic and vector search will enable DocuSign to extend its capabilities. We also signed a contract with a leading video-sharing platform for Elastic Cloud via the Google Marketplace to provide hybrid search, blending AI, vector search, semantic search, and Reciprocal Rank Fusion, or RRF, offering a platform that enables millions of users to create, edit, and share videos. The company is using the Elasticsearch Relevance Engine to serve as the core vector database for its millions of videos and associated metadata. The company has created and stored vector embeddings in Elastic in order to provide watchlist recommendations, leading to a better search experience. In Q2, we saw a significant increase in the use of ESRE. ESRE includes a built-in vector database, the ability to bring in your own machine learning models, and also ELSER, which is our own proprietary machine learning model for semantic search. This quarter, we saw a rapid adoption of ELSER, which we first released with the ESRE launch. With ELSER, customers are able to quickly implement semantic search without any model training to power generative AI use cases. With the release of the even more efficient ELSER Model 2 earlier this month, we expect to see this momentum continue. We also saw hundreds of additional customers starting to use ESRE for vector search use cases in Q2, building on our momentum from the first quarter. We are very pleased with this growth and are also excited by the progress we have been making on the innovation front. In Elastic 8.11, we delivered support for dense vectors with up to 400 dimensions, which is already greater than what embedding models require. We also delivered the first version of our machine learning inference API to improve the overall developer experience when building generative AI applications with Elastic. When search powers AI, customers are able to quickly build generative AI applications while reducing hallucinations at the lowest possible cost. Elastic's prospects as a key component of the modern IT stack for generative AI remain extremely strong. The second trend we saw in Q2 was customers continuing to consolidate onto the Elastic platform for multiple use cases. We had many key wins where we displaced incumbent solutions for observability and security and helped customers save on their overall IT spend while gaining even greater value through our many innovations. For example, we closed a multiyear 8-figure deal with a leading global wealth management company. Having previously used a legacy vendor, the company moved to Elastic Security for SIEM for deeper threat-hunting capabilities in order to keep up with data volume growth and threat sophistication. They are confident in our cloud-native technology, as well as the speed, scalability, and flexibility of Elastic and our generative AI capabilities. Additionally, a leading risk transfer company in Europe signed a multiyear subscription with us and replaced their legacy security provider. Elastic stood out as their preferred solution to fortify their organization against security threats and strengthen their security posture. By leveraging Elastic SIEM and tapping into our advanced capabilities such as cross-cluster search, the company can now effectively monitor and protect its large complex environment from a single pane of glass on one unified platform. As customers continue to consolidate onto our platform, we have been investing in capabilities that make it possible for customers to migrate easily from incumbent solutions to Elastic. In 8.11, we launched a powerful new piped query language, Elasticsearch Query Language, or ES|QL. ES|QL is designed to transform, enrich, and simplify data investigation with concurrent processing. ES|QL enables data aggregation and analysis across a variety of data sources from a single query, making it an incredibly powerful tool for data analysts, site reliability engineers, and security operations center analysts alike. The excitement from our customers on this capability in technical preview has been tremendous. We have also been investing in our AI Assistance for observability and security that make it possible for customers to leverage the power of AI to aid the humans involved in the detection, diagnosis, and remediation workflows in observability and security. These AI Assistance, which are in our enterprise subscription tier, are allowing us to leverage our leadership in AI even in the areas of observability and security. And this is something that we believe will continue to be a tailwind for us. The final trend in the quarter was around cloud consumption, where continued improvements helped drive cloud revenue growth. Customers remain focused on costs, but they have generally optimized their Elastic deployments and are now focused on driving new workloads to Elastic. This is an area where we continue to lean in to help our customers get the most out of Elastic. This customer-centric approach drives improved customer satisfaction and engagement and increases consumption over time. This drove our interest in acquiring Opster. Opster develops products for monitoring, managing, and troubleshooting Elasticsearch and OpenSearch. They are the creators of AutoOps, a powerful platform that provides deep insight to detect and resolve issues with cluster health, improve search performance, and reduce hardware costs. By joining forces with Opster, we will be able to help our customers get even more out of their Elasticsearch deployments and drive greater customer satisfaction and consumption. As we progress on our journey towards our serverless offerings, the management and monitoring capabilities that Opster has built will make our platform even more resilient and easier to use, and I'm very excited about this feature. Now on to our many product innovations in Q2. In addition to the ES|QL and generative AI innovations that I've already mentioned, the team delivered amazing capabilities across the Elastic platform. We added chat capabilities with the SQL integration to our AI Assistance. This allows customers to use natural language to explain a query and have the AI Assistant provide the ES|QL query syntax, explain what the query does, and provide a prompt to run the requested query. In observability, Universal Profiling became generally available. And we also integrated it with application performance monitoring or APM. With this new capability, users will be able to quickly correlate application performance issues with underlying system functions without needing to switch context from APM to Universal Profiling. When search powers observability, site reliability engineers have greater visibility across all signal types, reducing the time to resolve system issues. In security, we delivered Cloud Security Posture Management for Google Cloud. And now our customers can use Elastic to secure their workloads on Google Cloud in addition to their workloads on AWS. We also delivered out-of-the-box integrations with Wiz and Palo Alto Prisma Cloud to make it easier to get a view of the entire threat landscape in the Elastic platform. When search powers security, SOC analysts have greater visibility into difficult-to-detect threats, reducing the time to hunt and remediate threats. Finally, in search and generative AI, we delivered integrations with LangChain, LlamaIndex, and Amazon Bedrock, further simplifying the developer experience and providing our customers with greater flexibility as they build generative AI applications. Now on to our go-to-market focus and investments. We see a tremendous opportunity ahead of us as our search analytics platform becomes a key part of the modern IT stack for building GenAI applications. We firmly believe that our relationships with the major cloud hyperscalers will be a key factor in our success in the future. And towards that end, we are continuing to invest in these relationships. We just announced a new two-year global strategic collaboration agreement with Amazon Web Services. This will accelerate the integration of Amazon Bedrock into the Elastic AI Assistant, enabling customers to get richer, more contextualized, and relevant results by using their preferred large language model, coupled with the organization's unique IT environment and proprietary data sets. Also, building on our recent joint success with Google, we are accelerating and extending our joint go-to-market activities and technology integrations with Google Cloud. Our collaboration includes the powerful combination of the Elasticsearch Relevance Engine and Google Cloud's Vertex AI platform, which empowers developers with a scalable toolset to build privacy-first generative AI applications. Beyond our investments with cloud hyperscalers, we are also investing in broadening our global reach with 12 Elastic user conferences across major cities in the Americas, EMEA, and APJ. Based on the amazing customer reception we have seen to date, we expect over 5,000 in-person attendees and more than 100 customer and partner speakers to participate in ElasticON across these 12 events. Finally, I would like to reiterate our commitment to managing the business with discipline. We delivered a record non-GAAP operating margin of 13% for the quarter, which was better than our expectations, and we remain on track to deliver on our non-GAAP operating margin target for the full fiscal year. Janesh will talk further about this in a moment. To recap, we had an excellent quarter. I am pleased with how we managed the business with discipline, executed on our strategy, and I'm very excited about the second half of the year. At a time when companies are looking for ways to reduce costs and gain efficiencies without sacrificing innovation, especially around generative AI, Elastic's search analytics platform is becoming the natural choice for these businesses. We view generative AI as a massive tailwind that will continue to benefit our business in the years to come. In closing, I want to thank our team for their focused execution. And I also want to thank our customers, partners, and investors for their continued support and confidence. Now I'll turn it over to Janesh to go through our financial results in more detail.

Thanks, Ash. We once again delivered a strong quarter driven by consistent execution despite a complex external environment. We were pleased that we came in above the high end of our guidance for the quarter, both on the top line and the bottom line. We delivered 17% year-over-year growth in total revenue in the second quarter, with Elastic Cloud driving our strong results accelerating to 31% year-over-year growth. We continued our focus on profitability, delivering another record quarter with a non-GAAP operating margin of 13%, reflecting improved consumption trends versus Q1 and our strong investment discipline and demonstrating the leverage inherent in our business model as we continue to scale the business. As Ash mentioned, we continue to see strong customer engagement around generative AI use cases. We are increasingly seeing customers make technical decisions to select Elastic based on our product leadership position. The multiyear investments we have been making in generative AI are beginning to positively impact our go-to-market, especially around search-specific use cases, and we are positioned to be a long-term leader in this space. While we expect generative AI will present a meaningful revenue opportunity for us in the coming years, we believe it will take some time for the revenue from generative AI to become significant. During the second quarter, we saw continued improvements in cloud consumption patterns as customers increase their consumption against commitments that they had previously made. With that said, we continue to monitor consumption patterns against the backdrop of an evolving macro and geopolitical environment. While many customers have already gone through optimization of their consumption use cases, we do continue to see cost consciousness and spend management as themes in the market. Let's get deeper into the results for Q2 and our outlook. Total revenue in the second quarter was $311 million, up 17% year-over-year or 16% year-over-year on a constant currency basis. Subscription revenue in the second quarter totaled $288 million, up 19% year-over-year or 18% year-over-year in constant currency and comprised 93% of total revenue. Within subscriptions, revenue from Elastic Cloud was $135 million, growing 31% year-over-year on an as-reported basis or 30% year-over-year on a constant currency basis, reflecting the stronger consumption trends I just mentioned. Elastic Cloud represented 43% of total revenue in the quarter, up from 39% a year ago. Elastic Cloud revenue derived from month-to-month arrangements contributed 15% of total revenue, the same as in the prior quarter. Professional services revenue in the second quarter was $23 million, down 1% year-over-year on an as-reported basis and down 3% year-over-year on a constant currency basis. As we've said before, professional services revenue may fluctuate across quarters based on the timing of services delivery, and we do not expect it to vary significantly in mix over time. To add more context around overall deal flow, EMEA grew fastest during the quarter, followed by APJ and the Americas. We continue to see a healthy balance across the business based on geography solutions and verticals, and this diversification reflects the breadth and popularity of our platform. Moving on to customer metrics. We ended the quarter with over 1,220 customers with annual contract values more than $100,000. Looking at customer additions more broadly, we ended the quarter with over 4,230 customers above $10,000 in ACV and approximately 20,700 total subscription customers. Our net expansion rate, which, as you know, is a trailing 12-month lagging indicator, was approximately 110% in line with our expectation for the quarter. Now turning to profitability, for which I'll discuss non-GAAP measures. Gross margin in the quarter was 76.8% versus 76.5% in the prior quarter, reflecting a slightly higher subscription mix. Our operating margin in the quarter was 13%, which was better than expected. The strong operating margin performance was driven by our revenue outperformance and our continued focus on managing our expenses as we invest thoughtfully to drive future growth. Diluted earnings per share in the second quarter was $0.37. Our free cash flow on an adjusted basis was negative $3 million in the quarter or negative 1% adjusted free cash flow margin, in line with the expectations we had previously shared. As we stated on our previous call, there were some cash collection and payment timing movements between the first and second quarter, as well as one-time payments of $13 million in Q2 that related to previously completed acquisitions. For the full fiscal year, there is no change in our prior outlook, and we continue to expect free cash flow margin on an adjusted basis for fiscal '24 to be slightly above the non-GAAP operating margin for fiscal '24. We continue to maintain a strong balance sheet. We ended the second quarter with cash, cash equivalents, and marketable securities of $966 million. Turning to guidance. While we were very pleased with our outperformance in the first half of fiscal '24, we continue to be prudent as we plan for the rest of the year. Despite the many moving parts in the broader macro climate, we anticipate that business conditions will remain largely unchanged. We do expect to see growth in both self-managed and cloud subscription revenue. Additionally, though we are seeing customers ramp their consumption, and we've been very pleased with that trend, we believe it is appropriate to anticipate that consumption patterns may continue to fluctuate in the near term. In terms of operating expenses, as we execute in the second half of this year, it will be important for us to exit the year with an appropriate level of investment to secure our success for next year. Therefore, we continue to invest with discipline in the business, as we drive increasingly profitable growth on an annual basis. In addition to incremental organic investments in the second half, our model assumes approximately $12 million of seasonally higher expenses in the fourth quarter related to the timing of employee benefit costs and our engineering all-hands event. We have experienced similar seasonality in prior years, and these expenses were anticipated in the guidance that we had initially laid out for the year. With that background for the third quarter of fiscal '24, we expect total revenue in the range of $319 million to $321 million, representing 17% year-over-year growth at the midpoint or 16% on a constant currency basis. We expect non-GAAP operating margin for the third quarter of fiscal '24 in the range of 11.5% to 12% and non-GAAP earnings per share in the range of $0.30 to $0.32 using between 103 million and 104 million diluted weighted average ordinary shares outstanding. For full fiscal '24, we are raising our outlook and now expect total revenue in the range of $1.247 billion to $1.253 billion, representing 17% year-over-year growth at the midpoint or 16% on a constant currency basis. We expect non-GAAP operating margin for full fiscal '24 in the range of 10.25% to 10.75% and non-GAAP earnings per share in the range of $1.06 to $1.15 using between 102 million and 104 million diluted weighted average ordinary shares outstanding. Looking beyond this fiscal year, we continue to expect to grow revenue faster than overall expenses in fiscal '25, further expanding our non-GAAP operating margin. In summary, we are pleased with our strong performance in the first half and are confident in our outlook for the rest of the year. And with that, let's go ahead and take questions.

The first question is from Brent Thill with Jefferies. Please go ahead.

Thanks. Ash, I'm curious if you could just talk about the timing of revenue impact with AI and how you expect that to unfold. And quickly for Janesh, there were a few client questions around NRR lower, new logo growth also slower, but now seeing good strength in cloud, can you just break that apart and give us a little better view of what you're seeing? Thanks.

Thanks for the question, Brent. First of all, I am very pleased with the overall performance in Q2, and particularly, like I talked about in the prepared remarks, the adoption of ESRE. And as you know, ESRE includes not just our native vector search capability but so much more beyond that. And we are seeing customers really adopting that incredibly well. We also saw in the quarter that customers are making their purchase decisions for all kinds of use cases, looking at the leadership position that we have in generative AI and seeing that the innovations that we are driving there are going to help them in all kinds of use cases. In terms of the monetization, what I'd say is it's still early days. It's going to take some time for customers to ramp the usage of these generative AI workloads. So, it isn't a significant contribution to revenue at this time, but we are pleased with the contribution to consumption that we're already seeing in these early phases from these GenAI use cases. Let me turn it to Janesh for the second question.

Hi, Brent. So, on the net expansion rates and cloud consumption trends, when I just step back and look at Q2 overall, we are very happy with our overall performance. When you look at the numbers on revenue and on cloud growth, there was a lot for us to be pleased about. The net expansion rate, as you know, is a lagging indicator and it's a trailing 12-month measure. So, even as cloud consumption ramps up like we saw here in Q2, it will take some time for that consumption to be fully reflected in the net expansion rate. And that's why when I think about the business, I usually look at revenue as the best indicator of current performance. And so, I think the net expansion rate can continue to move a few points in either direction in the near term. But generally, we expect that the trends in consumption over time should alleviate some of the downward pressure that we had experienced in the net expansion rate over the past few quarters. The other piece that you mentioned was on consumption overall. If I just step back and think about some of the consumption trends we saw, pretty healthy patterns across industries and geographies. It was broad-based. Our sense is that optimization has stabilized. Customers are still cost-conscious, as we mentioned, but generally, they are where I think they want to be on optimization. So, we see customers ramping their consumption towards their commitment levels, and we are very pleased that we're able to help them scale their usage and realize the value of our solutions. So, those are some of the puts and takes, and we're quite happy with Q2 and looking forward to the rest of the year.

Thanks. Welcome back, Anthony.

Hi, thanks. Congrats from me as well. Two quick questions, one for Ash and one for Janesh. Ash, if you think about it, you're obviously the strong player in search, and now with the AI capabilities and ESRE, you kind of, you know, are able to revisit that installed base. What do you see in terms of the overall reviving that search kind of client base and kind of reengaging with them a lot more here? And what are you seeing there in pipeline, customer conversations, etc.? Because that seems to me like a nice big opportunity to just kind of revisit and reengage with clients there. And the second question for Janesh is, you talked about the consumption trends. On that note, if I look at the implied guidance for Q4, that does look like a very small additional number coming in there. Is there anything specific on Q4? Is that just conservatism? Thank you.

Yes, Raimo, thanks for the question. I think, like I mentioned even in my prepared remarks, generative AI is really driving a resurgence of interest in search. I have been on the road quite a bit meeting with our customers. We recently, in just these past few months, had multiple ElasticON events, first here in San Francisco, then in Frankfurt, then in Amsterdam, literally hundreds of customers, many customer speakers. So, I had the opportunity to meet with many of our clients there. Also at AWS re:Invent earlier this week, I was there in person meeting with our customers and some of our partners. Across the board, what we are hearing, what I'm seeing is a significant interest in generative AI. A lot of it is around use cases that we would traditionally bucket into the category of search. We are seeing a lot of interest in trying to completely change customer experiences, trying to completely change support experiences. There are use cases across the board in every vertical. So, that's something that we feel really good about in terms of the long-term position and the long-term view for us, and over the long haul, what it can do in terms of TAM expansion in the overall area of search. The other thing that I'll say is, right now what I'm seeing is a lot of the use cases that are being put into production are internal-facing. Customers are building chat experiences or applications that are viewed by internal support engineering teams, or their internal SRE teams, or their internal employee portals, and so on. That's largely because they are getting a level of comfort with these large language models. That's also where they really find a lot of value in Elastic, because the ability that Elastic provides to ground these large language models in the context of their businesses is something that they see a lot of value from in terms of reducing hallucinations and so on. Over time, we believe that that's going to then make it possible for them to expand to external end-user-facing use cases, which is going to be another expansion of the overall opportunity. So, very excited, and absolutely this is something that we are leaning in on. And let me turn it to Janesh on your second question.

Hi, Raimo. As I think about the guidance and trying to unpack that, maybe just commenting on the second half first, then I'll touch on Q4 as well. Overall for the second half, the way we approached it was just recognizing that we've seen good, strong consumption patterns here as customers are scaling their usage up to their committed levels. If I think about the external environment, the macro is generally stable. As we said, cost consciousness continues to be a theme in the market and is important for customers. We've benefited from that to a degree as customers have made greater commitments to us. But we've also seen in the past that can cause consumption to fluctuate if customers drive operational changes. So, we've simply considered that possibility of potential consumption fluctuation in the future as we built our guidance. Just for clarity, we've not seen any big shift in the external environment, but we just think it's best to plan prudently. We're executing really well, we're excited, and we're confident about the rest of the year. Specific to Q4, I'll just point out that the only unique thing about Q4 is it's a slightly shorter quarter for us. Given that 2024 will be a leap year, Q4 will have 90 days instead of 92 days. That's just something that creates a bit of a headwind in Q4.

Hi guys. This is Harshil on for Ittai. Can you hear me?

Yes.

Got it. Earlier this year, you gave us an update on the $2 billion revenue target and how that timeline had been extended a bit with the challenging macro. But now, with the environment seemingly a bit more stable, consumption starting to improve, and the momentum you're seeing with generative AI, I'm just curious if there’s anything you can share on that timeline? And, you know, versus eight months ago, has that maybe moved a bit forward?

Hi, Harshil, this is Janesh. We were through that $2 billion goal sometime back, but the way we think about this fundamentally is that we've got a significant opportunity ahead of us, and we are working hard to prosecute that opportunity. You've seen tremendous momentum here from the standpoint of the overall business, and particularly in terms of cloud growth as we address that opportunity. All of that is additionally fueled by the momentum that we are seeing in generative AI. We don't want to get too far ahead and start to predict future revenue growth beyond this year at this stage. But there's no question in our minds that we are working hard to build a multi-billion dollar Company at scale in the future. And we'll provide you with appropriate updates as we go on that. But for now, we are focused on executing this year and feel very good about the back half of the year.

Got it. That's helpful. And then just on NRR, is this a 110% level? Is this an area where we should expect it to bottom out? And as we look to fiscal '25, what levers do you see that could get NRR back up to the historical level?

As I mentioned just a couple of minutes ago, because the net expansion rate is a lagging indicator, even as cloud consumption ramps, it just takes time for that to be reflected in the net expansion rate. I think it can move a couple of points in either direction in the near term. But over time, what will help drive the net expansion rate is increasing consumption. As we move forward, as consumption ramps, that will alleviate some of the downward pressure that we had experienced previously, and growth in cloud and our rates of consumption will help overall as we progress into the future.

Oh, great. Thanks, guys. Congrats on the quarter. Ash, it seems like ESRE is opening up a lot of customer conversations. There's a lot of positivity. How often are these conversations expanding into something more than just AI, say, in security, observability? Do you think that AI as the entry point to drive larger deals across the board is a motion that could accelerate your growth? And then one for Janesh: any way to understand the cloud consumption trends so far in November in Q3?

Hi, Pinjalim, thanks for the question. The way we see it is that, in the areas of search, there is a clear expansion of the TAM that is likely going to happen just given the momentum that we're seeing, the resurgence of interest in search and the kinds of use cases that people are both imagining and starting to build. That's going to be something that we feel in the long term is going to be very material. In the areas of observability and security, the AI assistants that we have launched and the compelling capabilities that we've delivered, the ability through natural language to auto-generate ESQL commands and understand what the queries mean, and to have the system automatically execute them through the prompt makes life easier for a site reliability engineer for observability or a SOC analyst for security. They can do their work while the system guides them through the whole journey, from detection to diagnosis to remediation. We feel that’s very powerful. That's something that our sales teams will often lead with when they're having a conversation around observability and security. I talked about the fact that we have had many customers consolidate onto our platform, where we displaced incumbents. A lot of those discussions we lead with the AI Assistant and how we showcase our platform. So that’s definitely something that I'm very excited about.

In terms of the observations on November, I think it's a little too early to tell. November isn't even over yet. As we've said before, there can be fluctuations within a single month as we look at the pool of customers. So we tend not to rely too much on a single month of data. I can't share a specific view on November just yet, but I can tell you that the trends we experienced in the quarter that I described earlier were broad-based, and we felt very good about that in Q2.

Great. Thanks very much. Janesh, last year you had a really strong booking quarter as customers began to increase their commits. How should we think about that comp for this quarter?

Hi, Brad, your voice was a little bit muffled, but I think you were asking about year-over-year comps from a commitment standpoint. Customers are continuing to make commitments to Elastic. We've seen that strength in commitment as we think about just ongoing execution that we have, as we think about the engagement that our field teams have with them. Ash talked about all of the trends in generative AI that are continuing to provide a good tailwind to that. We feel very good about our overall position in front of customers. In terms of how that translates into specific commitments for Q3, it's too early to tell for that. We aren't going to provide forward views on commitment or bookings-oriented measures. We feel very good about the revenue outlook we've provided, and I think that continues to be the primary measure for us in the business.

That's great. And just a quick follow-up on something you said earlier on the SaaS side. As customers are scaling to their committed levels, are those customers at their committed levels still below that, and is there an opportunity to move higher, or are they consuming in excess of that? Thanks.

Yes, it's a broad pool of customers, so different customers will be at different stages. The point I was making earlier is that, as customers have been ramping, they're approaching, in general, the levels of commitment they had. There are obviously some customers within that that are consuming above those levels, and then it becomes a good opportunity for us to drive expansion conversations with them. There are some customers that are still below those levels, but on balance, we've seen customers continuing to ramp as the quarter has progressed.

Great. Thanks for taking my questions, and congrats from me as well. Ash, I was wondering, on the initial GenAI interest, obviously, there's a lot of other competitors out there that have solutions. I'm sort of curious, when customers are faced with a choice, what is the tipping factor thus far? Is it the role-level security, or I’m just curious, are there some commonalities of why Elastic versus others at this point?

Yes, absolutely. I'd say I'd break it down to roughly four categories of clear differentiation that our customers keep telling us they see in our product and platform as they evaluate us against all the options out there and the reason why they choose us. The first and foremost is, and I hear this very consistently, that they find that our vector database functionality is absolutely stellar in terms of how it scales, in terms of the fact that it's built deep into the platform, and it's built in such a way that you get the benefit of all the other functionality that we've built over the years. So that’s first and foremost something that we hear over and over again. The second thing that we are very proud of is, generative AI is more than just having a vector database. Because there's so much more that you need to do in terms of finding the most relevant information to pass as context to the large language model. That requires more than just a vector database; it requires you to have semantic search and hybrid search functionality because often that will result in the most optimized and most correct, most relevant information, more advanced features like Reciprocal Rank Fusion. And this, when you talk about context, there are also other things like personalization, geolocation, filtering, all of these aspects, along with privacy and role-level security, which you mentioned. The third, I'd say, is areas around just our openness. We've always had this mindset of being open as a company, providing our customers a lot of choice. We are LLM-agnostic. We have excellent partnerships with all the major cloud vendors: Azure OpenAI, Google Vertex AI, and AWS Bedrock. And we also support a lot of the open-source community LLMs, like Llama 2 from Meta. That just means that when somebody uses us, they get a platform that gives them the choice of LLMs because we don't believe there's going to be one LLM to rule them all in the future. That choice matters to customers. Lastly, the incumbency: so much of the unstructured, complex, messy data that is critical is already sitting in Elastic clusters on tens of thousands of customers. For them, it becomes the easy button. They're able to just use our platform, use all that data that they've already ingested in, and now build these GenAI applications on top of it. That makes it a very compelling proposition.

Super comprehensive. Thanks for that. And then I guess, you know, obviously it's still early and the acquisition of Splunk hasn't gone through yet. But I'm curious, has there been any initial feedback from customers on what that might mean for existing Splunk customers? I'm just curious if that's starting to show up in any customer conversations that you're seeing.

I think I've said this many times: when it comes to the core markets in observability and security that we play in, whether it's log analytics for observability or security analytics or SIEM for security, we have very few competitors that operate at our scale. I'm not going to talk about any one particular competitor. But what I will say is that, given that we are one of very few, our ability to take share from others by having customers move to our platform, consolidate onto our platform because we have a more scalable offering. We are really differentiating our offering with generative AI, with the AI assistance that we have built. Probably one of the most exciting things is the Elasticsearch Query Language, right, ESQL, the uptake and the interest in that has been just phenomenal. Not only is it easy to use, but it’s a piped query language that gives them the ability to iterate over their work, and it's making it super easy for customers to migrate off of existing incumbent solutions onto Elastic. Everything that's happening in the market right now, we feel is really supporting our ability to continue to have a very strong future.

Hi, thank you so much. Happy holidays and congratulations on the quarter. On this generative AI thing, I'm curious to get your updated thoughts, Ash, on how what's the monetization strategy for generative AI? At one level, looking at the compelling explanation you have, it makes Elastic more accessible, so it's easy to start using the system using natural language search. So, ESQL becomes a lot more accessible. Or is the market with generative AI opening up brand new use cases? Is it that the accessibility of the platform becomes better so the monetization of the TAM becomes easier? Or is it that and new use cases that you could not otherwise target with the existing Elastic architecture that open up more avenues? How do you put a price tag on your generative AI efforts?

Yes, Kash. Thanks for the question. Let me first address the use cases; I'd break it into two categories. One is for search; in the area of search, generative AI is broadening the TAM. There are lots of things that were not possible or were not easy in the past that now suddenly become possible. One example would be video search or image search at scale. That works incredibly well with vector search and hybrid search but not so much with traditional lexical search. Another example is the kinds of customer service use cases people are trying to build with GenAI. These are experiences that just would not be possible with just search in the past. Now, with the combination of semantic search and hybrid search, customers can build these conversational applications to improve the overall search experience. That's driving interest and implementations that we believe are really exciting for the future. It’s pretty TBD how much, but we will get a better sense as we progress through the quarters on just how much of an expansion of the search TAM gets created by this wave of generative AI. When you think about security and observability, I don't think it's so much of the TAM increasing, but rather generative AI is making it easier for newer types of users to use the Elastic platform to solve specific use cases. It also allows us to differentiate our platform better. We're focused on improving usability, and generative AI is just making that much better. Regarding monetization, every time you're using ESRE, you are fundamentally using the machine learning capabilities on our platform, which are in our paid Platinum tier. Our AI assistance for observability and security are only available at our enterprise tier. These machine-learning jobs for generative AI tend to be a lot more compute-intensive, so there are various different vectors for us to monetize the work that we're doing.

Hi, guys, thanks for taking the question. I wanted to ask a question on the Opster acquisition. Two parts here: could you give us a sense of maybe the revenue scale and cash used for the acquisition? And then a little bit more strategically? When looking at the Opster website, I saw things such as cluster health visibility and improving search performance. But I also saw that Opster helps reduce hardware costs, which sounds a little cannibalistic in a sense. How should we be thinking about the long-term strategy for Opster from a monetization standpoint?

Hi, Koji. Maybe we can take those in reverse order. Ash, maybe you can touch on the strategy first and then I'll touch on the financials.

I'm super excited about the Opster acquisition. AutoOps really lets you monitor and manage the overall system cluster and optimize it, right? You can detect issues before they happen. You ensure that the system stays healthy at massive scale, which is important for our customers. That drives customer satisfaction and encourages customers to do more with our platform and drive more consumption. It's really a play around consumption to ensure that customers can do more with our platform and keep consuming in a way that is good for them and good for us. Your point about optimizing the hardware; that's a key part of our overall strategy, too, because we monetize by having these capabilities in our paid tiers and in cloud. Customers naturally adopt higher tiers and Elastic cloud, and we want our customers to spend less on infrastructure, but we monetize all that by having them move to higher tiers, which increases their spend on Elastic. We believe that it's a win-win for customers and us. That makes this a compelling proposition.

In terms of size, Opster is a small but mighty team. We are not expecting any meaningful revenue contribution from Opster. As Ash described, the intent is really to fold the Opster technology into the broader Elastic Stack. Even in terms of expenses, we've just built that into the model that we've already provided.

I was hoping you guys could drill down a bit on the security market, specifically SIEM applications, as we're starting to hear from others about a SIEM replacement cycle?

Our position in security analytics or SIEM remains very strong. I talked about our success in the quarter. We've seen this in the past several quarters of getting customers to consolidate onto our platform, displacing incumbents. We are seeing the benefits of both the capabilities, the scalable functionality in our platform, and some of the newer GenAI functionality through the assistance that we've delivered. The market dynamics seem to be playing in our favor. We are very excited about it and feel very good about the future.

Thank you. Nice quarter. I just want to ask more specifically about ESRE. I know it's only available in the platinum and enterprise tiers. So I'm wondering, are you seeing customers already upgrading to those tiers or any sort of uptick in new logos that are landing with those two tiers?

We've generally seen a steady increase in the adoption of our higher tiers over time, particularly on the enterprise tier, and we continue to expect that this will help drive growth for Elastic Cloud looking ahead. As I think about all of the additions to the tiers and what drives customers to the higher tiers, clearly a lot of the generative AI functionality is helpful in that regard. The security and observability AI assistance will only be in the enterprise tier. We have added features to our higher subscription tiers over time, like ML, and we have seen a steady increase over time in our adoption of higher tiers.

Okay, thank you. And then I just had a quick question on, as it relates to your vector search. I know you've had it for a number of years, and I felt like where customers are actually storing their data in an Elastic data lake, it makes your vector search more appealing to them, specifically in a security use case. Are you competing with MongoDB in vector search use cases, where they're looking specifically for vector search?

When you think about what it takes to build generative AI applications, vector search is a component of the overall solution, not the whole solution. What we see is that when you're building generative AI applications, you need effective connectors to bring all this unstructured data into your environment. You need to provide capabilities like semantic search and hybrid search and re-ranking capabilities. There is also a need for filtering, geo-location, and often other kinds of personalization capabilities. All of these things that are all about relevance and context go way beyond just vector search. Customers are increasingly looking to our platform because we have that complete breadth of capabilities that makes it possible for them to build generative AI applications on one platform. What I will say is that we don't see the database vendors showing up as competition. There might be cases where all your data is in a particular database, and you have some very simple use case, where you just want to search across that data. That's very native to that particular platform. For us, we are going after the broader market of customers trying to build generative AI applications that require way more than just a vector data store, and that’s what we provide, soup to nuts.

Thanks for taking my question and congrats on the great execution, Ash and Janesh. Welcome back, Anthony. Ash, you touched upon the evolution in Elastic's go-to-market strategy before, the shift towards a more efficient and unified vision for customer engagement and partnerships in light of recent realignments, including the consolidation under the CRO. Today, you highlighted generative AI beginning to positively impact the go-to-market around search. Can you talk about which of these factors like the hyperscaler partnerships or user conferences directly spreading awareness are bigger drivers currently? And in terms of the strategic realignment of go-to-market, how are you positioning effectively in the AI landscape now? Thanks a lot.

What I would say is that all of the things that we are doing matter, right? Our ability to best satisfy our customers comes from the fact that we can provide them unique, differentiated functionality with the integrations with all the ecosystem partners. Our relationships with these ecosystem partners like cloud hyperscalers allow us to reach and service those customers very effectively. Our focus not just on commitments, but also on consumption, all of that is paying off. It's about having a cohesive strategy. I'm very excited about the fact that the team has been executing very well. I'm very proud of the work that they've been doing, and we feel really good about both the second half of the year and the future.

Thanks for taking my question. Congrats on the quarter. I just want to ask a quick one on cloud. Great performance this quarter. As we look at Q4, should we expect similar levels of seasonality versus last year? I think last year was when the cloud cost optimization started in April?

Hi, Kingsley, this is Janesh. Overall, when we look at the approach we've had, we had really strong performance in the first half of this year. We've seen customers start to ramp their consumption towards the levels that they had committed, and we've continued to see them make strong commitments. When I talked about guidance, the way we've approached it is simply to consider that it's still an economic environment out there that is stable, but similar to what it was before. There’s room for fluctuation in consumption patterns. We're trying to balance the strength of our execution in the first half against any potential risks that might be out there. For clarity, we haven't experienced anything different yet, but we're just being thoughtful as we build our plan for the year.

Hi, thank you. If I could just build off Kingsley's question there. I know that there have been a number of people who are asking about the guidance construction and what it means for Elastic Cloud. My question is, does your guidance currently anticipate the gap between commitments and consumption widening as we get into the second half of this year versus what was delivered in the second quarter?

I think the answer to that question mathematically would depend on what level of commitments we are assuming for Q3 and Q4. I'm not going to unpack that level of detail. Consumption is ramping quite nicely. We're doing everything we can to help customers derive value. It's worked nicely for us for the last few quarters, and we'll continue to work hard towards that end for the next couple of quarters and beyond.

Got it. If I could just ask a quick follow-up for Ash here, but on the generative AI adoption, I'd be curious to hear what kind of customers you are seeing adopt? Are these potentially digital natives or mid-sized organizations that might be nimbler? The reason I ask is, we've picked up in our checks that some of the larger enterprises are still running evaluations to understand GenAI, how to orchestrate these workflows, just given the compute intensity behind them. Anything incremental on the flavor of customers that are starting to adopt these technologies would be helpful.

We are seeing success across the board, large customers as well as digital natives, across verticals. I gave at least two examples in my prepared remarks, noting large customers. One was DocuSign and the other was a video-sharing platform. I would say that generally, even larger organizations, one of the reasons we are successful in those environments is that we are proven in those environments. Many of these clients already trust our platform; they have been doing large-scale search applications on our platform in the past. Now, as they see the innovations we are driving, it's a much faster process for them to get productive and build GenAI applications on our platform than in other places. We've seen that over and over again where they might start using a pure vector database, and they quickly realize that they need more than that, choosing our platform. I feel really good about it, and it’s much broader than just digital natives.

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

Thank you all very much for joining our call today. I could not be more excited about the opportunity and our unique position in generative AI as a leading AI-powered search analytics platform. We are pleased with our strong performance in the first half and confident about the second half of the year. We look forward to updating you on our progress as we go. Have a great rest of the evening and thank you.

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