Ashutosh Kulkarni
Analyst · Jefferies. Please go ahead
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 and what 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 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 life cycle 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 that will ultimately serve as the core vector database for its millions of videos and associated metadata. The company has created and stored a vector embeddings in Elastic in order to provide watch list 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 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 as well as 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, improved 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 kinds of 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 power 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 and 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 tool set 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 manage 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, Elastics' 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.