Ash Kulkarni
Analyst · JPMorgan. Please go ahead
Thank you, Anthony. Good day, everyone. And thank you for joining us on today's call. Elastic delivered another strong quarter. Our results reflect our continued execution, our ability to deliver differentiated product innovations, our maniacal focus on our customers, and our attention to managing the business with discipline. The trends we saw over the first-half of the fiscal year continued to drive momentum in our business in Q3. First, customer interest in generative AI remains strong, and as customers become more educated about what it takes to build generative AI applications, they're increasingly able to appreciate the advantages of our platform relative to pure play vector database vendors. Second, we saw continued momentum in platform consolidation as customers chose the Elasticsearch platform to displace incumbent solutions for multiple use cases, particularly in log analytics and SIEM. Lastly, we saw continued stability in cloud consumption patterns as customers increased their consumption against their previous commitments. These trends reinforce our confidence in the business and in our future growth as more companies choose our search analytics platform as a core part of their IT infrastructure stack for log analytics, SIEM, and Gen AI applications. I'll talk more about these trends and share some customer success examples driving our growth in a few minutes. First, let me start with a review of our financial performance. I'm pleased with our strong momentum and execution that drove our third quarter results. In Q3, revenue grew 19% year-over-year, with Elastic Cloud growing 29% year-over-year, driven by continued customer traction in the cloud, and consolidation onto the Elasticsearch Platform. We also exceeded our profitability guidance with a non-GAAP operating margin of 13%. Turning to the broad trends we saw this quarter, as I met with customers around the globe, I saw a strong desire to leverage AI to improve business processes and elevate customer experiences. At the same time, companies remain focused on finding ways to reduce costs. In a sense, it's all about gaining efficiencies without sacrificing innovation. This is where Elastic shines. With the Elasticsearch platform, businesses can unlock the full potential of all their data to gain insights that drive innovation, optimize customer experiences, and inform strategic decisions. In the area of generative AI, customers are starting to advance their capabilities in leveraging retrieval augmented generation or rag patterns for building GenAI applications using existing and emerging language models. This is leading them to fully explore the total set of functionalities needed to build enterprise class GenAI applications. Advanced features like hybrid search, personalization, and re-ranking with reciprocal rank fusion, document level permissions, security, and much more. All of these capabilities, in addition to our leading vector search functionality, and the fact that we are already the incumbent platform for data for tens of thousands of customers means that we are able to significantly lower the barrier for businesses to build their own generative AI applications. This is our asymmetric advantage, and as Generative AI and RAG are becoming better understood, our edge is becoming more pronounced. In the third quarter, we once again added several hundred customers using the Elasticsearch Relevance Engine or ESRE. ESRE allows customers to build Generative AI applications quickly without complicated and expensive model training. This is a big reason why customers turn to us for Generative AI. One example of this is our long-time customer Consensus, an AI-powered search engine that aggregates and distills insights from more than 200 million peer-reviewed papers from the semantic scholar database. They use Elasticcloud for advanced artificial intelligence, semantic, and text search. Consensus 2.0 is powered by ELSER. Their users have benefited from increased accuracy and relevance of search results and new GenAI features such as a summarization of the top 10 studies based on integration with OpenAI's GPT-4 model. In Q3, we also expanded our business with Stack Overflow, the largest and most trusted online community for developers, which replaced its previous vector database with Elastic. The company chose Elasticcloud for our scalability, differentiated functionality, and integration across the ecosystem. Stack Overflow is leveraging Elastic's vector and semantic search capabilities to deliver a more human-like generative AI-powered question-and-answer experience to developers via its overflow AI product. We also continue to see customers choose our platform, because they expect to use our ESRE functionality in the future. In other words, they see us as the right choice for the needs today, as well as for the future. As an example, a cloud-based document management company for legal professionals signed a multi-year deal with Elastic this quarter. With over 6 billion searchable documents, the company chose Elastic for our innovations, performance, and ability to power search across their entire platform. Previously, using a competitor's offering, they moved to Elastic because of our market leadership and to modernize the search experience to align with their customers' expectations by leveraging Elastic's vector search capability to enhance the user experience. Beyond generative AI, we noted that customers are continuing to displace incumbents and consolidate onto the Elastic Platform for observability and security, which is the second trend I talked about earlier. The Elastic observability and security solutions are built on top of our Search Analytics Platform, with Elasticsearch as the foundation. Our platform has the unparalleled ability to quickly ingest all kinds of data to index it at extreme speed and at petabyte scale and make it searchable, and then allow for all kinds of advanced correlations, AI-powered searches and ad hoc analytics. This gives customers the ability to centralize onto a single platform for all use cases that require this kind of advanced search and analytics. This is a big reason for our success in displacing incumbent solutions especially around log analytics and SIEM or security analytics. Our recent innovations including our AI assistance for observability and security are making it even more compelling for customers to move to our platform. This quarter, we closed several multi-million dollar deals where we displaced incumbent solutions for observability and security. Our value and our innovation is resonating across industries, as we continue helping customers save on their overall IT spend, while helping them gain even greater value from our innovations. As an example, a top U.S.-based bank chose Elastic as a desired SIM platform to replace their legacy vendor. The drivers behind the selection included platform speed, performance, scale, and Elastic's rich set of security features. They also chose Elastic for our innovative storage-tearing searchable snapshots capability, which allows the bank to retain important security logs for longer regulatory retention periods at dramatically reduced storage cost. We also expanded business with the U.S. state agency for elastic security. The agency initially started with Elastic for search and then in Q3 chose Elastic to replace their legacy security vendor for SIEM, enabling them to increase support for their security operations center. The scope of Elastic's ingest capabilities, search speed, platform functionality, stability, and reporting capabilities allows the agency to gain and maintain visibility across their environment and multiple agency branches and correlate alerts across a broad security tool set. Now, turning to products and innovation, we continue to invest in capabilities that make it possible for customers to migrate easily from incumbent solutions to Elastic. On our last call, I mentioned the launch of our powerful new piped query language, Elasticsearch Query Language or ESQL. Even as we continue to enhance this new capability, we have seen tremendous interest from our customers with approximately a thousand customers trying it out since we launched in November. Our latest release of Elastic 8.12 in January also included several key enhancements, including scalar quantization, which is a vector search optimization technique that delivers performance improvements across several critical metrics. It dramatically improves enterprise-level scalability, allowing customers to store 4 times as many vectors in RAM, while also improving overall indexing speed and reducing query latency by up to 2 times. Additional enhancements to search concurrency resulted in speed ups across a very broad set of query types, including vector similarity and full text search, as well as a 40% reduction in latency for analytical queries. In Elastic Observability, we brought several capabilities to general availability, including the enhanced Elastic AI assistant for observability, SLO monitoring, and mobile APM support based on open telemetry. In Elastic Security, we continue to enhance our market-leading Elastic AI Assistant for security, introducing real-time alerts with natural language interactions that enhance the way security analysts approach alert triaging. This results in a more efficient, effective security operation that is adept at navigating the complex cybersecurity environment. In cloud security, we added support for Microsoft Azure, in addition to our existing support for AWS and Google Cloud for cloud security posture management. On the go-to-market front, we drove continued momentum in Q3 through our participation in AWS re:Invent and our ElasticON conference events that allowed us to connect with thousands of customers, prospects, and users worldwide. We have now concluded six of these ElasticON events and will be holding another six in our fiscal Q4. And as a final, but important highlight for the quarter, I was pleased to announce that Mark Dodds joined Elastic as our new Chief Revenue Officer. Mark leads all of Elastic's customer-facing functions, including global sales, customer success, solutions architecture, professional services, ecosystem and partnerships, and sales operations. Mark brings extensive go-to-market experience to our executive team as we continue to drive momentum in Generative AI and growth across all segments of our business. I'm excited about everything that Mark will do for us in the coming years, as we push to capture the full opportunity ahead of us as a company. In closing, I'm very pleased with how we perform this quarter. The innovations we are driving into our Search Analytics Platform, the momentum we are gaining around Generative AI, and the traction we are seeing in customers consolidating onto our platform is continuing to increase our confidence in our future. We see a future where our Search Analytics Platform becomes a core part of every IT infrastructure stack for gaining insights from all data, especially in the context of generative AI. I want to thank the Elastic team for their resolute focus and the entire Elastic community for their unwavering commitment. Now, with that, let me turn the call over to Janesh.