Elastic N.V.

Good day, and welcome to the Elastic First Quarter Fiscal 2024 Earnings Results Conference Call. All participants will be in listen-only mode. Should you need assistance, please signal a content specialist by pressing the star key followed by zero. After today's presentation, there will be an opportunity to ask questions. To ask a question, you may press star then one on your telephone keypad. To withdraw your question, please press star then two. Please note, today's event is being recorded. I would now like to turn the conference over to Janice Oh with Investor Relations. Please go ahead.

Thank you. Good afternoon, and thank you for joining us on today's conference call to discuss Elastic's first quarter fiscal 2024 financial results. On the call, we have Ashkel Carney, Chief Executive Officer, and Janesh Morjani, 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, our expectations regarding the demand for our products and solutions in 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 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 second quarter fiscal 2024 quiet period begins at the close of business on Tuesday, October 17, 2023. On September 5, 2023, we will be participating in the Goldman Sachs Communicopia Technology Conference. With that, I'll turn it over to Ash.

Thank you, Janice, and thank you all for joining us today. I'm pleased with how we performed this quarter. we had a strong start to our fiscal year with our performance exceeding our stated expectations across both revenue and non-GAAP operating margin. In Q1, revenue grew 17% year-over-year, with Elastic Cloud growing 24% year-over-year. We ended the quarter with more than 1,190 customers with annual contract values over 100K. As customers continue to adopt Elastic as their data analytics platform of choice, for addressing multiple real-time search use cases. And we continue to manage the business with discipline to deliver a non-gap operating margin of 9.9%. Elastic has always had a singular mission, enabling everyone to find the answers that matter, from all data, in real time, at scale. The versatility of our platform, the built-in AI capabilities, such as the Elasticsearch Relevance Engine, or ESRE, and our ability to excel at multiple real-time use cases across search, observability, and security on our data analytics platform have all made Elastic a natural choice for our customers as a core element of their IT stack. Our land and expand strategy continues to serve us well, and our long-term opportunity remains robust. In Q1, we saw two distinct trends within our business. The first is around generative AI. Generative AI and its intuitive approach to interact with massive amounts of information and generate new content is driving a resurgence of excitement around enterprise search. Businesses are recognizing the opportunity to create new customer and employee experiences and drive efficiencies in various business processes through the use of AI-powered search. This is opening up new opportunities for Elastic. To build generative AI applications that work within their environment and with their proprietary data, businesses need the ability to provide accurate context in real time to large language models, or LLMs, and to do so in a way that doesn't violate their privacy or security policies. This requires a platform that can allow businesses to use their own or third party ML models to generate embeddings from their data irrespective of the type of data. Store these embeddings in a vector store at very large scale and then efficiently search across these vectors in real time to enhance LLM responses by providing context using retrieval augmented generation. The platform needs to ensure that this vector retrieval enforces data privacy with document-level permissions and takes context such as user privileges, personalization, geolocation, and other factors into account. The platform also needs to be flexible enough to enable hybrid search using a combination of vector, semantic, and textual search techniques to ensure the most relevant results possible. Elasticsearch with Esrae delivers this entire set of capabilities in a single platform. It does so in the same platform that is already being used by tens of thousands of organizations worldwide for real-time search use cases. Our proven scale, performance, and advanced enterprise features like document-level permissions, built-in security, and hybrid search with reciprocal rank fusion makes us a highly differentiated and ideal choice for these generative AI use cases. In Q1, we saw significant activity around generative AI with a number of customers choosing Esrae as their platform for building generative AI applications using our vector search and hybrid search capabilities. As an example, a US-based Fortune 100 global media and technology company has integrated Esrae with their own locally hosted large language model to enable their ticketing system to now deliver contextual answers to questions from their customers. This is projected to enable their team to solve about 50% of their help desk tickets through this automation made possible by the power of generative AI. Another example is a leading file sharing service that is using Elastic's hybrid search capabilities to power a new AI-powered universal search tool. The combination of vector search and textual search enables them to bring a significantly superior search experience to their customers across all subsidiaries and applications. With Elastic's generative AI and machine learning capabilities at its core, its tool learns and evolves alongside its users, continuously improving as they use it. Another example is the leading AI platform, Labelbox, that uses Elastic to power one of its most popular tools, Labelbox Catalog, enabling teams to accelerate and streamline machine learning model development through optimized search experiences. With Elastic's fast and rich search capabilities, Labelbox customers can undertake unstructured data searches in a fraction of the time compared to its previous search solution, which ultimately helps them to capitalize on the possibilities of AI. Similarly, companies are also using Elastic to enable things like forensic video analysis at scale. One leading telecom equipment company is using their own large language model, coupled with Elastic's vector search capabilities, to power their cloud-based video search solution, enabling them to better identify bad actors and provide real-time security. These are just a few of the many examples of customers using us for generative AI today. Elasticsearch is the most popular platform for search, and as customers build contextual generative AI applications, they are naturally choosing Elasticsearch and Esrae to provide relevance and context based on their private data. Today, We have hundreds of paying customers using SRA for vector search, and the conversations we are having with our customers gives us confidence about our continuing traction in this space. We anticipate that as customers start to put more and more of these use cases into production, generative AI will be a real tailwind for our business. The second distinct trend in our business is the continued push by customers to consolidate onto the Elastic platform for multiple use cases. In Q1, customers continued to make large multi-year commitments as they sought ways to lower their total spend without sacrificing innovation by bringing more workloads from other incumbent solutions onto Elastic. We continue to leverage our competitive strengths in our core areas of search, log analytics, and security analytics to drive our land and expand strategy. As an example, in Q1, we closed a multi-year deal with Texas A&M University for Elastic Cloud on AWS. The university previously deployed a competitor solution, but moved to Elastic for security and observability. The customer chose Elastic for ease of use of a single platform without needing multiple licenses. and search results in high speed and relevance for all their data, enabling them to rapidly and effectively solve their business challenges. They use Elastic to search through, analyze, and secure all of their data from a unified platform while optimizing costs and meeting compliance requirements. We also closed a multi-year deal for Elastic Observability with one of the largest multinational communications and entertainment companies in the world. They started with a small deployment of Elastic next to a competitor's solution, but consolidated onto Elastic to become the enterprise standard for its observability platform. This company chose Elastic for its flexibility and scalability across different data types and leverages advanced features such as searchable snapshots and machine learning to help them take an AIOps approach to the data they're ingesting into Elastic. This quarter, we also renewed an expanded business with one of the world's leading internet domain registrar and web hosting companies. A longtime Elastic customer, the company previously used a competitor solution, but moved to Elastic, and in Q1, signed a multi-year contract for Elastic Cloud on AWS. The company has consolidated multiple tools across logs, metrics, and APM in Elastic Observability to effectively monitor thousands of online services for customers while reducing mean time to resolution and streamlining operational costs as its business continues to scale. As we have discussed previously, our customers routinely tell us that our platform delivers a much higher value than competitive offerings, and these advantages, along with our innovative AI-powered data analytics platform are enabling us to compete very well in this environment. Now, onto our products. In Q1, we continued our focus on innovation and delivered on several key capabilities to our platform and our solutions. One of the most significant announcements in Q1 was the release of the Elastic AI Assistant, powered by Esrae. This AI assistant, which helps guide analyst investigations and remediation is in beta for security and in technical preview for observability. We continue to enhance capabilities in Esrae and delivered new hybrid search capabilities with the industry-leading implementation of Reciprocal Rank Fusion or RRF to combine vector, keyword, and semantic techniques for better results. We are also continuously improving the speed and performance of the Elasticsearch platform. And we did work in Q1 in this area that resulted in faster and more relevant outcomes for search aggregations, for cross-cluster search, and for dense vector search. This included support for native implementations of vector search using hardware accelerated SIMD instruction sets, which yields even faster queries and 30% greater indexing throughput. In the area of elastic observability, we integrated our time series data streams, or TSDS capability, with popular elastic observability integrations, such as Kubernetes, NGINX, AWS Kinesis, and Lambda, enabling the potential to reduce storage needed for metrics data by up to 70%. In the area of elastic security, we extended support for advanced entity analytics with the general availability of lateral movement detection. On the go-to-market front, we continue to focus on our partnerships with the major cloud hyperscalers. And I'm pleased to highlight that we recently earned top accolades from each of the three hyperscalers, Microsoft, AWS, and Google Cloud. Specifically, we were named the Microsoft Commercial Marketplace Partner of the Year and the AWS US ISV Rising Star Partner of the Year. And just this week, we were honored to receive the Google Cloud Global Technology Partner of the Year Award. These awards from all the three cloud hyperscalers are a reflection of the strength of our relationships with these cloud partners, the deep product integrations we have built with them, and the success we are achieving together in driving growth for our businesses in the market. Customers are making significant multi-year commitments to our platform through these cloud marketplaces as they leverage Elastic as an AI-powered data analytics platform for multiple real-time use cases across search, observability, and security. Finally, I would like to again highlight that Q1 was a continued demonstration of our commitment to managing the business with discipline. We delivered a non-GAAP operating margin of 9.9% for the quarter, which was significantly better than our expectations, and we remain on track to deliver on our non-GAAP operating margin target for the full fiscal year. In closing, I want to thank our team for their dedication and continued focus and execution. I also want to thank our customers, partners, and investors for their continued support and confidence. Our conviction in the long-term opportunity in front of us remains strong. It is based on the strength of our relentless innovation and continued customer confidence in Elastic. Generative AI is opening up new opportunities for us that we expect to capitalize on in the coming quarters and years. And as cloud optimization is stabilizing, we expect to continue making progress on our stated goal of driving growth with profitability. With that, I'll turn it over to Janesh to go through our financial results in more detail.