Elastic N.V.

Good afternoon and welcome to the Elastic fourth quarter fiscal 2024 results conference call. All participants will be in listen only mode. Should you need assistance, please signal a conference 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, this event is being recorded. I would now like to turn the conference over to Anthony Luskri, Vice President of 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 fiscal 2024 financial results. On the call, we have Ash Kulkarni, 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, 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 we issued earlier today, including the slides posted on the investor relations website and those more fully described in our filings with the Securities and Exchange Commission. We also discussed 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 2025 quiet period begins at the close of business on Wednesday, July 17, 2024. We will be participating in the Bank of America Global Technology Conference and the Baird Global Consumer Technology and Services Conference during the week of June 3rd. and the Mizuho Technology Conference and the Rosenblatt Technology Summit during the week of June 10th. With that, I'll turn it over to Ash.

Thank you, Anthony, and thank you, everyone, for joining us on today's call. Elastic delivered yet another strong quarter and a great finish to the fiscal year. We once again outperformed against our guidance on both revenue and profitability metrics. In Q4, revenue grew by 20% and cloud revenue grew by 32%, and we delivered an operating margin of 9%. We also continued to execute on our land, expand, and consolidate motion, and we grew the number of customers spending over $100,000 with us to over 1,330. A year ago, we kicked off FY24 by releasing our Elasticsearch Relevance Engine, including our vector database and our sparse encoder model, ELSER. Throughout this past year, we continued to strengthen our position as the platform of choice for building real-time generative AI or GenAI applications. And I'm happy to share with all of you that we now have well over 1,000 distinct paying customers using our vector database and retrieval augmented generation or RAC capabilities for building GenAI applications. I'm particularly pleased with the strong Gen AI adoption we are seeing among our largest customers, with more than 145 of our customers with annual contract values of over 100,000 already using our Gen AI capabilities. The number of Gen AI customers in this category has more than tripled in the last year, and this represents the fastest pace of adoption we have seen for any new major capability we have introduced in the past. We believe that in time, every organization, big and small, will leverage the power of AI to transform their businesses. This is a significant market opportunity for us that will play out over the long term. Every customer interaction I had in Q4 involved customers actively seeking to explore and use GenAI for business benefit. Our customers are using GenAI to improve all kinds of business processes and to transform customer and employee experiences. This includes customers from newer digital native companies like RoboFlow to more mature enterprises, including some of the largest companies in the Fortune 100. RoboFlow is using the Elastic platform at tremendous scale for building innovative GenAI applications. The RoboFlow platform is used by hundreds of thousands of engineers to create data sets, train models, and deploy computer vision models in production. RoboFlow uses the Elastic Vector Database to store and search billions of vector embeddings at extreme speed. In Q4, within the enterprise segment, one of the world's largest financial services institutions expanded with a multi-year, eight-figure deal with Elastic. The company uses Elastic for search and observability in a center of excellence with multiple use cases across the business. The company is now using Elastic's vector search capabilities in a strategic new application to provide highly accurate AI-based real-time recommendations for wealth managers to support the organization's most valuable clients. Not only will clients receive better service from wealth managers, but the managers will be able to double the number of clients that they can support. The company chose Elastic over other vendors for this new generative AI use case because of our innovative technology, superior time to value, and their ability to use existing in-house expertise in technology to quickly deploy this cutting edge interactive application. Another example is a large international electronics company in Asia. which expanded their existing use of Elastic and shows Elastic for vector search and retrieval augmented generation, or RAG, to power their internal employee support system. The new LLM-based Q&A system for the semiconductor division is expected to improve both employee productivity and product quality. Another large global financial services company signed an expanded deal this quarter to use Elastic's GenAI capabilities for bank policy search, helping all employees find and understand the organization's complicated, interconnected regulatory policies and procedures. This will increase efficiency and productivity across the business, as well as help improve the overall regulatory posture. As the search AI company, Elastic is uniquely positioned to help our customers capitalize on the transformative possibilities that generative AI brings. We bring together the precision of search and the intelligence of AI so customers can build innovative applications. The strong and sustained adoption we are seeing for our GenAI capabilities and our continuing pace of innovation that expands our competitive moat in this area reinforces our confidence in our ability to be a long-term beneficiary of the massive wave of business transformation being brought about by GenAI. In the areas of observability and security, we are helping customers harness the power of Search AI to make their organizations more resilient by bringing more intelligence and automation to their observability and security solutions. In Q4, our AI strengths, including our AI assistance for observability and security, continue to help us displace incumbent observability and security vendors and consolidate customers onto the Elastic platform. As customers look to consolidate onto a few platforms to reduce costs while increasing their pace of innovation with AI, Elastic has continued to be a beneficiary, thanks to our relentless focus on innovation and our obsession with customer centricity. For example, one of the largest global providers of insurance, annuities, and employee benefits signed a new deal for Elastic Cloud on Azure. the company consolidated multiple tools onto Elastic as part of its AIOps strategy, allowing teams to be faster, more efficient, and more accurate. Elastic was chosen over competitors because of our ability to ingest any kind of data, aggregate and correlate all data on one platform, as well as automate observability using the Elastic AI Assistant. Now turning to products. In Q4, our team continued to deliver some highly anticipated capabilities to further expand our competitive moat in the areas of Search, GenAI, Observability, and Security. We launched a first-of-its-kind Search AI Lake and announced the technical preview of our new Elastic Cloud Serverless offering, which is built on top of the Search AI Lake architecture. Data lakes of the past offered low-cost, durable data storage, but there was a compromise when it came to speed and the ability to search for relevant information across all of the data in the lake in real time. This has historically inhibited the use of data lakes for real-time applications. Elastic's Search AI Lake is a significant innovation that addresses this need. It's an exabyte-scale cloud-native architecture with built-in search and vector database capabilities. It is optimized for real-time, low-latency applications, including RAG, observability, and security. Our Search AI Lake and the technical preview of our serverless offerings are currently available on AWS. Over the next couple of quarters, we plan to expand this offering to all three major cloud hyperscalers and across the major geographical regions, at which point we will make this offering generally available. We see this as an exciting new chapter for Elastic Cloud, as it greatly simplifies the overall user experience, and we expect this to be a growth driver for cloud in the coming years. In the area of Search Engine AI, we delivered several new capabilities to further differentiate our offering. starting with significant enhancements to the Elasticsearch Open Inference API. These additions include integration with Cohere's vector embedding and re-ranking APIs, as well as the embedding API for OpenAI on Microsoft Azure. We also delivered improvements to our core vector database, including concurrent multi-segment graph search and native code optimizations that contributed to significant improvements to vector search query speed. We released vector search optimized instance types on both Google Cloud Platform and Microsoft Azure, completing our effort to support optimized hardware profiles on all three hyperscalers. We also released native support for custom learn-to-rank models, allowing customers to deploy trained models that improve search relevance based on user behavioral data directly in Elasticsearch. In addition, Microsoft announced that Elasticsearch was added as an officially supported vector store and retrieval augmented search technology for Azure OpenAI service on your data. Similarly, Red Hat also announced their support for Elasticsearch as an officially supported vector store in OpenShift. In the area of observability, Elastic has become a platform of choice for customers who are standardizing on OpenTelemetry. Earlier in FY24, we donated the Elastic Common Schema, or ECS, to the Cloud Native Computing Foundation, or CNCF's OpenTelemetry project, as its standard schema for logs. And now we've open sourced our profiling agent under the Apache 2 license and contributed it to CNCF, pending their approval. Additionally, we also delivered support for AWS Bedrock and the Anthropic Cloud 3 model in our Observability AI Assistant, improving the overall AI Assistant experience and increasing choice for our customers. In security, we unveiled our newest innovation, Attack Discovery, powered by Search AI at the RSA Security Conference. Attack Discovery correlates, enriches, sifts through and prioritizes actionable intelligence from a flood of alerts using the unique rag capabilities of our platform, significantly reducing the effort SOC analysts have to put into the alert triage and investigation process. It presents the user with an attack view that focuses on the few relevant attacks that matter, as opposed to the underlying alerts, which can have way more noise than signal. On average, SOC teams receive thousands of alerts daily and spend many hours manually triaging these alerts, leaving a significant portion of potentially critical threats to slip through the cracks. By leveraging Elastic's AI assistance, attack discovery, and other AI-powered ways to remediate or prevent issues, we enable security practitioners to do their jobs more efficiently. while helping our customers remain resilient with less cost and less effort. Our customers have told us that they see this patent-pending innovation as a true game changer for the SOC. The SIM space is evolving again, this time to an AI-driven security analytics platform, and we are leading the charge in this evolution. Lastly in security, Elastic Security Labs also delivered our LLM safety assessment along with detection rules to help customers protect themselves from prompt injection attacks and other threats to the secure adoption of large language models and other Gen AI technologies. In closing, I couldn't be more proud of our team and the consistent way we have executed our strategy while managing the business with discipline throughout FY24. We continue to strengthen our position as the platform of choice for building real-time GenAI applications, and we see increased momentum as customers displace incumbent solutions and consolidate onto Elastic for more and more use cases. Our customers, partners, and the developer communities are what drives our focus and fuels our innovation. As the Search AI company, Elastic is exceptionally well positioned to take advantage of the transformative technology shift that Genitive AI is assuring in. With that, I'll turn it over to Ganesh to go through our financial results in more detail.