Voyage AI & MongoDB Partnership - Voyage AI was acquired by MongoDB approximately 3-4 months ago [1] - The partnership aims to create a single data platform for embedding, re-ranking, query augmentation, and query decomposition [29][30][31] AI-Powered Search & Retrieval - AI-powered search finds related concepts beyond identical wording and understands user intent [7][8][9] - Embedding quality is a core component, with 95-99% of systems using embeddings [12] - Real-world applications include chatting with codebases, where evaluation is crucial to determine the best embedding model and LLM for the specific application [14][15] - Structured data, beyond embeddings, is often necessary for building powerful search and retrieval systems, such as filtering by state or document type in legal documents [16][17][18] - Agentic retrieval involves feedback loops where the AI search system is no longer just input-output, but can expand or decompose queries [19][20] Future Trends - The future of AI-powered search is multimodal, involving understanding images, text, and audio together [23][24][25] - Instruction tuning will allow steering vectors based on instructions, enabling more specific document retrieval [27][28]

Financial Data and Key Metrics Changes - The company positions itself as a "Search AI company," focusing on providing high-performance solutions for storing, searching, and analyzing vast amounts of data [5][6] - The core technology is centered around Elasticsearch, which serves as the primary data storage and processing engine [8] Business Line Data and Key Metrics Changes - The company markets its offerings in three main areas: developer tools, observability products, and security solutions [9][12] - The observability product combines unstructured log messages with structured metrics and traces to identify operational issues [10] - The security product is described as a modern SIEM that goes beyond traditional capabilities, addressing the increasing complexity of security threats [11][49] Market Data and Key Metrics Changes - The company has seen a diverse range of use cases for Elasticsearch, from traditional search applications to more complex scenarios like transaction tracking and logistics [15][19] - The advent of AI has expanded the potential applications of Elasticsearch, with a focus on semantic and vector search capabilities [21][25] Company Strategy and Development Direction - The company aims to simplify the developer experience by providing out-of-the-box tools for building generative AI applications [36][37] - There is a strong emphasis on integrating AI capabilities into their products, including features like vector search and semantic search to enhance search relevance [25][26] - The acquisition of Keep Alerting is seen as a strategic move to enhance workflow automation capabilities in both security and observability [64][66] Management's Comments on Operating Environment and Future Outlook - Management acknowledges that customers are at various stages of maturity in adopting generative AI applications, with some already in production while others are still experimenting [39][40] - The importance of providing accurate and contextually relevant information is highlighted as critical for the success of AI applications [72][75] Other Important Information - The company has established partnerships with major AI model providers to enhance its offerings and ensure compatibility with various AI frameworks [32][68] - The focus on security is underscored by the need for per-user and per-document security measures, which are critical for enterprise applications [80][81] Q&A Session Summary Question: What is Elastic's overall strategy regarding AI? - The company is focused on building core components for developers while also utilizing these components in their observability and security solutions [23][24] Question: Are customers still in the experimental stage with generative AI applications? - Customers are at different maturity levels, with some already deploying generative AI applications in production [39][40] Question: How does Elastic position itself in the security space? - The company provides a comprehensive security suite, including a modern SIEM with prebuilt detection rules and AI-powered features [46][49] Question: What is the integration with NVIDIA's enterprise AI factory about? - The partnership aims to leverage NVIDIA's capabilities for running AI workloads, enhancing the company's offerings in the AI space [90]