Thank you, Eric, and thank you all for joining us today. Elastic had an excellent Q1 and a strong start to the fiscal year, delivering 20% revenue growth for the first quarter, surpassing the high end of our guidance. Sales-led subscription revenue, calculated as subscription revenue, excluding monthly Elastic Cloud, grew by 22% and was driven by strength in both our cloud and self-managed offerings. Our growth was supported by the ongoing demand for our highly differentiated search AI platform and our sales team's solid execution. The inherent leverage in our business model and our disciplined execution continue to fuel our profitability, resulting in a non-GAAP operating margin of 16%. We ended the quarter with more than 1,550 customers spending over $100,000 as enterprises continue to choose Elastic for their search, observability and security needs. Amidst today's rapidly changing global landscape and with AI now clearly shaping technology decisions, our Q1 performance directly demonstrates the value that the Elasticsearch AI platform delivers to customers. Market demand for our solutions has strengthened, contributing to our overall success this quarter. Our strong market position is further deepened by the operational strength of our sales team with the territory changes we made now fully benefiting our execution. Our go-to-market momentum is building across the board. In the U.S. public sector, we are seeing signs of stabilization. In U.S. public sector win from the quarter, an intelligence agency adopted Elasticsearch and Observability for their AI-powered enterprise services, consolidating on to Elastic due to our reputation as a trusted mission partner and owing to the strength of our AI capabilities. Our strategic agreement with the U.S. General Services Administration, or GSA, which we signed in Q1 and ongoing progress on FedRAMP high certification for Elastic Cloud are helping build positive momentum. Both initiatives are boosting interest among U.S. civilian and defense agencies who aim to modernize with scalable, productive and efficient technology. With our sales team fully primed for this environment, we are well-positioned to execute and capitalize on the federal government's efforts to digitally transform and advance its infrastructure with our innovative platform. A year ago, we revamped our sales segmentation model to build for the future, focusing our team on expanding enterprise accounts and landing high-potential mid-market customers, measures which are proving very effective today. This tactical alignment continues to drive progress in our strategic segment, where we enable generative AI application development and consolidation for our largest customers. For example, a global professional services organization expanded their commitment by choosing to migrate to Elastic Cloud in Q1. They rely on Elasticsearch as their vector database to power 40 different internal and client-facing applications. The transition to Elastic Cloud will enable them to achieve greater operational efficiencies and seamlessly access our more advanced search features. Critically, as they advance their gen AI initiatives for clients, Elastic's advanced search technology will be instrumental in unlocking insights from unstructured data at scale. In Q1, we saw significant activity around gen AI with many customers choosing Elastic as a runtime platform for building gen AI applications using our vector database, embedding and reranking models, MCP server and other platform capabilities for building conversational AI and agentic applications. Now over 2,200 Elastic Cloud customers are using Elastic for gen AI use cases with over 330 of these customers spending $100,000 or more annually. In Q1, we added more million ACV Elastic Cloud customers using Elastic for gen AI use cases than the prior 2 quarters combined. We are also excited to witness AI-native businesses being built on Elastic to introduce entirely new business models. In Q1, an AI-native music company expanded their use of Elasticsearch, upgrading from a monthly cloud subscription to an annual agreement as they see growing adoption of their applications. They leverage Elastic to manage vast amounts of song data, supporting full text and semantic search for millions of users as they continue to grow and launch new products. The company chose our Search AI technology for its performance, speed and ability to scale alongside their rapid growth, which in turn drives their Elastic consumption. Our customers' requirements for speed, scale and relevance drives our continued investment in product features to ensure that every query happens in real time with accuracy and reliability. This quarter, we launched new capabilities to improve performance and cost efficiency of our vector database, now making our Better Binary Quantization or BBQ and ACORN-1, a smart filtering algorithm, available to all users by default. BBQ and vector search with ACORN-1 helped us land a 7-figure expansion deal with a global wholesale provider of machinery parts for Elasticsearch and observability. They rely on Elastic to drive their e-commerce platform, which consists of over 1 million stock items and a database of nearly 50 million SKUs. The retailer is implementing a hybrid search system, which requires a platform capable of interpreting natural language queries and performing exact and semantic matches to deliver more accurate and relevant search results. They chose Elastic due to our extensive experience in retail search transformation and our customizable search AI functionalities, all within one platform. AI is reshaping the software stack and LLMs are becoming the new operating system for defining business logic. In the past, most software relied on data and data platforms optimized for structured data. Today, LLMs operate on all data and need a data platform optimized for all forms of data, structured and unstructured, text in spoken and programming languages, audio, video, graphs, vectors and more. Elastic is the world's leading vector database. Crucially, our continued leadership stems from the foresight that what matters most is relevance in data retrieval, irrespective of the language, type and messiness of the data. When you get relevance right, you provide accurate context to LLMs to do their job, and this accuracy matters even more as Agentic AI gets used for automating increasingly more complex business tasks. With Elasticsearch, relevance is our true competitive advantage, fortifying a defensible moat around our business. As enterprises build more agents and develop software in new ways, the importance of getting context and search relevance right will only grow. This is why we have invested for years in developing our own embedding models, reranker models, data chunking strategies and more, all with the goal of being the absolute best at search relevance. It is this innovation that gives us the confidence to be the leading data retrieval and context engineering platform for the AI era. This also forms our asymmetric advantage in the other markets we play in, including observability and security. In anchoring our observability and security solutions on Elasticsearch, we fuse the immense power of Search AI into both and automate the observability and security processes of our users with our AI capabilities like attack discovery, auto import and our AI assistance for observability and security. It is precisely these advanced capabilities that contributed to our security business achieving strong results this quarter. As AI reshapes the SIEM landscape, Elastic Security unifies SIEM and XDR into a single AI-powered platform, extending protection across customers' data infrastructure and eliminating the need for multiple stand-alone tools. In Q1, 1/3 of our new and expansion wins in security involved competitive displacements. In one such deal from the quarter, one of the largest integrated academic health systems in the U.S. selected Elastic Security to replace its existing SIEM solution. This 7-figure expansion deal marks the customer making a strategic shift from an incumbent solution towards a more scalable AI-driven security approach, driven by their need for a flexible platform to unify data. Elastic stood out due to our ability to support a broad set of data sources and our market-leading AI features, including attack discovery, demonstrating our leadership in defining the future of SIEM. Our consistent vision of solving security as a data problem while driving innovation in AI positions Elastic at the forefront of the market. In doing so, we are being rightly recognized by independent research, and we are delighted that Elastic has been named a leader in the Forrester Wave: Security Analytics Platform in Q1. Our promise in security is further demonstrated by Elastic Security's 100% score in AV Comparatives Business Security test for endpoint security, where we were the sole participant among 17 vendors to achieve a perfect score in both the real-world protection and malware protection tests. In pairing Elastic anti-malware prevention with our ransomware defense and leading SIEM features, we achieved world-class XDR. And our innovation has not stopped. Earlier this month, we introduced the Elastic AI SOC Engine or EASE. Many SOC teams today rely on SIEM and endpoint detection and response or EDR, solutions that generate valuable alerts but lack mature built-in AI capabilities to conduct investigations. EASE integrates with existing SIEM and EDR platforms to connect our advanced AI tools into their environment, allowing for AI-powered alert correlation with attack discovery and access to our AI assistant. Architected as an agentless integration on top of a customer's existing stack, EASE is an on-ramp to Elastic Security. This commitment to AI-driven innovation extends beyond security. Our AI capabilities and powerful analytics also earned us recognition as a leader in the 2025 Gartner Magic Quadrant for Observability Platforms for the second year in a row. Elastic's leadership reflects how we are transforming observability from a reactive tool into a solution for real-time investigations through the power of our Search AI platform. We are shipping new tools like EASE and our recently announced Logs Essentials, a new low-price tier of Elastic Observability within Elastic Cloud Serverless for customers wanting a fully managed offering. Serverless is now generally available on all 3 cloud hyperscalers, including on Microsoft Azure. Serverless is gaining traction with contributions surpassing our Q1 targets as more customers adopt this deployment. The Elasticsearch AI platform meets customers where they are with deployment options for cloud, hosted and serverless and self-managed environments. This quarter, I visited India, Australia, Singapore and Japan to meet with customers across numerous industries. Despite vastly different businesses, every conversation I had revealed the common desire to do more with their data. Enterprises are all looking to leverage their information more effectively. This consistent feedback reinforces the universal need for powerful data solutions like ours, especially one that is optimized to address the need for search relevance and context in an LLM- centric world. In closing, Q1 was an outstanding quarter, fueled by focused execution and strong demand. Our platform is more differentiated than ever, providing us a competitive advantage in gen AI and platform consolidation across all industries. We have the ability to win in every market where we are playing, and I'm excited to see our progress unfold. This quarter's performance highlights the talent and dedication of our team. Navam and I are truly grateful for the continuous hard work Elasticians put in daily. Thank you as well to our customers, partners and investors for their ongoing support and trust. I'll now turn it over to Navam to review our financial results in more detail.