Thank you, Anthony, and thank you all for joining us today. Our Q3 results reflect ongoing momentum across all aspects of our business, led by our strong sales execution, continued market demand for our products and our relentless space of innovation. With strong contributions across all solution areas, search, observability, and security, we delivered an outstanding quarter, outperforming our guidance metrics. Total revenue grew 17% year-over-year with cloud revenue growing 26% year-over-year and our non-GAAP operating margin represented 17% of revenue. The number of customers spending over $100,000 with us increased to over 1,460 during the quarter, demonstrating the strength of our land and expand motion. Consolidation and generative AI are powerful tailwinds, driving momentum at Elastic and at the forefront of our interactions with customers and prospects, especially as customers continue to prioritize innovation and efficiency across their businesses. During the quarter, we saw continued progress in our go-to-market motion. At the start of this fiscal year, we implemented field segmentation changes that increased our focus on landing and expanding enterprise and high-potential mid-market customers. These changes resulted in some unanticipated sales execution issues in Q1 that we have since been addressing. Our performance in Q3 demonstrates that we are now back to the levels of sales execution that we have seen in the past and we are even starting to see the expected positive impact from the earlier segmentation changes. Q3 performance benefited from our maniacal focus on these customer segments and deal flow remained strong during the quarter as we grew commitments from new and existing customers across all of our solutions. To that point, we have already added significantly more customers spending over $1 million with us through the first three quarters of this fiscal year versus all of last year. Generative AI is enabling organizations to extract value from unstructured data, documents and logs. Search is core to value extraction, and we saw outperformance from search in Q3 with our search business once again accelerating year-over-year. We are seeing an evolution of search with customers moving from textual search to semantic search and then building conversational applications using retrieval-augmented generation or RAG. As enterprises experiment with and adopt agentic workflows to automate multi-step business processes, the importance of search for powering AI will continue to grow. Customers are choosing the Elastic search AI platform as an essential layer on which to build all of these flavors of new search-powered applications and we expect this momentum will continue to form a tailwind for our business for many years to come. Our vector database resonates with customers. In addition to our best-in-class vector database, we are taking a distinct approach, offering customers an efficient way to create, store and search vector embeddings beyond those provided by point solution vector databases. In Q3, we signed a seven-figure deal with the digital-native career platform, displacing a competitor's vector database as the company scales their business globally and creates new Gen AI-based customer experiences. The Elastic Search AI platform provides a complete search experience within a single platform, allowing the customer to evolve and deploy critical functionality without the complications of managing third-party APIs. We are seeing a positive impact from our leadership position in Gen AI on our business. In the quarter, we signed five deals of greater than $1 million in annual contract value where customers are building Gen AI applications using Elastic, building upon our momentum in Q2. Now over 1,750 Elastic Cloud customers are using us for Gen AI use cases with over 270 of these customers spending $100,000 or more with us annually. We believe that as more companies leverage large language models to create new customer experiences, automate business processes involving unstructured information and evolve work streams toward agentic AI use cases, we will benefit. Elastic has the power to bring all these pieces together to be the runtime platform for Gen AI applications that simplifies developer experiences and drives greater efficiency and accuracy. Outside of Gen AI, we also see strength with our observability and security solutions as customers continue to consolidate onto our platform. In observability, our strategy centers on logs, knowing that they are a rich data source for monitoring mission-critical systems and often represent the messiest data that is challenging to analyze. Elastic excels at transforming logs into understandable, searchable and analyzable formats, a key reason for why we win with customers. Our unified data store with our emphasis on extremely efficient storage makes it possible for customers to correlate log data with metrics, APM traces, and other observability signals at a massive scale, making our solution incredibly compelling for enterprises. Our investments in pattern analysis, machine learning, and GenAI reflect an evolution from traditional monitoring to a modern approach that reveals the unknowns in complex systems. New product releases like logsdb index mode continued to differentiate our solution from competitors. In another competitive win from the quarter, we signed a seven-figure deal with an industry leader in smart water management. The customer expanded its use of Elastic Search and Elastic Observability to enhance operational efficiency and customer service. We power their analytics and billing platform, which ingests millions of water meter readings daily, enabling them to proactively identify anomalies and resolve issues to ensure their systems run effectively. Logsdb index mode was a key factor in how we've outperformed two competitors with features that optimize data, ordering, and storage and reduced query latency, showcasing our scalability and ability to deliver accurate results. Additionally, they have now started to build RAG powered conversational app on our Search AI platform to strengthen customer service. In security, AI-driven security and information management or SIM transforms the modern SOC by automating and simplifying processes, helping practitioners work more efficiently and effectively than traditional SIM solutions. In 2024, we released our attack discovery solution, leveraging large language models to automate threat discovery. I'm pleased to report that we are seeing strong interest from customers looking to enhance their SOC operations and we have received positive feedback from industry analysts around this ground-breaking functionality. In a new seven-figure deal, a military unit responsible for overseeing software capabilities and development for U.S. government use shows Elastic Security SIM and endpoint capabilities to support military operation centers. Elastic was selected over competitors for a compelling total cost of ownership. These SOC environments ingest terabytes worth of logs per day and Elastic's cross-cluster search and replication capabilities facilitate efficient workflows for the customer. The customer intends to implement attack discovery to streamline alerts once their Elastic Security deployments are fully operational. Customer consolidation onto our platform drove multiple wins during the quarter as we continue to benefit from the secular tailwind. By helping customers reduce complexity and drive efficiency at a lower total cost of ownership, we are securing solid commitments and becoming an increasingly strategic part of their IT infrastructure. Madrid Digital, a government agency responsible for the digital transformation of one of Europe's largest capital cities, signed a new agreement with Elastic in a seven-figure multi-year deal for Elastic Observability. The customer moved from an open-source version to Elastic Cloud to consolidate multiple tools onto a single platform and modernize its infrastructure. Madrid Digital provides diverse services for its 7 million constituents, requiring a solution to effectively monitor over three terabytes of logs per day and reduce the average resolution times for technical incidents. They chose Elastic Observability over competitors due to our scalability and product features like cross-cluster search and our AI assistant. Now turning to product innovations during the third quarter. We released Elastic Cloud Serverless, which is now in general availability on AWS and technical preview on Azure with general availability expected in March. Though in the early stages of our journey, we are starting to see momentum with customers. Elastic Cloud Serverless is the fastest way to access Elastic Search, Elastic Observability, and Elastic Security. We offer customers a dedicated offering for each solution with distinct pricing and experiences to match different underlying personas. One Elastic Serverless customer, SAP Concur, highlighted that it takes virtually no time to set up a new project, emphasizing its autoscaling capabilities. Our industry-first Search AI Lake serves as the foundation of our serverless architecture, allowing for low latency querying across all data with the precision of search. As a fully managed offering, Elastic Cloud Serverless reduces the configuration burden for our customers so that they can run faster to their desired end state. We will launch support for Google Cloud instances as we continue to expand this offering to all three major hyperscalers in the coming months. The general availability of Elastic Search logsdb Index Mode, which is available in our enterprise tier was another milestone release during the quarter. LogsDB Index Mode makes Elastic Search more efficient and encourages customers to do more with Elastic. By optimizing data storage, indexing, and management, we help our customers extract more value from logs while reducing the total cost of ownership. Similar to our release of searchable snapshots in 2020, the cost savings of logsdb Index Mode pushes customers towards the enterprise tier, incentivizing customers to move over workloads from competitive products and consolidate more onto our platform. Data consolidation onto Elastic's Search AI platform unlocks more value from the underlying data as customers leverage search AI across our solutions. Customers are expanding their use of Elasticsearch due to logsdb Index Mode. During the quarter, a global software company and longtime Elastic Search customer upgraded to Elastic Cloud Enterprise from the Platinum tier to access all capabilities of logsdb Index mode in a seven-figure deal. The customer's previous logging estate was fragmented with multiple tools and inconsistent standards, hindering efficient analysis and troubleshooting. Elasticsearch will be providing better logging infrastructure at a compelling total cost of ownership, allowing them to consolidate tools and modernize the observability stack. The customer also chose Elasticsearch as their end-to-end rack solution to jumpstart their AI journey and accelerate their ability to ship GenAI features rapidly to their customers. Our Rerank model differentiated our platform from competitors, improving accuracy and reducing latency while remaining affordable. We released the Elastic Rerank model in tech preview during the quarter. Our Rerank model boosts search results with more relevance. For RAC, providing precise context from the user's data to large language models helps ensure accuracy of responses and reduces costs by improving the semantic relevance of each query. Similar to the blueprint of our ELSER model, we designed Rerank to be high-performing with relatively low resource requirements. While our architecture supports integration with third-party models, we are also building our own embedding and Reranking models, up-leveling our platform to a holistic solution where customers can adopt certified components from Elastic into their infrastructure. Q3 brought several major opportunities to connect with and learn from our customers, developers, IT professionals, and partners. We continued our ElasticON conference in Amsterdam, Paris, and London, where our team and I were on the ground engaging with thousands of customers and prospects interested in learning more about how to get the most from Elasticsearch AI platform. In November, we attended AWS Reinvent, where we were honored with the AWS Global Generative AI Infrastructure and Data Partner of the Year award, a testament to our strong partnership with AWS and recognition of our work to help customers develop and scale their GenAI capabilities. Today, we are also announcing that Navam Welihinda will be joining Elastic as our CFO starting February 28. Navam was most recently the CFO of Grammarly and prior to that spent seven years at HashiCorp, where he helped lead them through many milestones, including their IPO and successful growth to over $650 million in revenue run rate. Prior to HashiCorp, Navam spent time in finance leadership roles at IBM and Deem, before which he spent time in venture capital at Sierra Ventures and Inside Venture Partners. I'm very excited to have Navam join our senior leadership team, especially given his experience with opensource and consumption-based businesses. We have an incredible finance team here at Elastic and I'm confident that together with Navam, they will help guide Elastic forward to newer and greater business milestones towards becoming a generational company. I would also like to thank Eric Prengel, who has done a tremendous job as Interim CFO these past several months and who continues to be a trusted senior leader within the company. Eric will now report to Navam and continue leading finance strategy and FP&A in addition to some new responsibilities. I'm looking forward to working very closely with both him and Navam in the years ahead. In closing, I am energized by the momentum building in our business and our strong performance this quarter. Thank you to all of our employees for their dedicated execution and to our customers, partners, and investors for their ongoing support and confidence. I'll turn it over to Eric to review our financial results in more detail.