Core Insights - Elastic announced a new integration for Amazon Bedrock AgentCore, enhancing observability for AI agents and applications within the Elasticsearch platform [1] - This integration enables site reliability engineers (SREs) and developers to monitor, optimize, and troubleshoot agents operating on Amazon Bedrock AgentCore [1] - Elastic Observability facilitates monitoring by ingesting all logs and metric signals related to AI agents and applications [1]

Corporate Overview and Q2FY26 Financial Results November 20, 2025 Forward Looking Statements; Use of Non-GAAP Measures This presentation and the accompanying oral presentation contain forward-looking statements that involve substantial risks and uncertainties, which include, but are not limited to, statements regarding our expected financial results for the fiscal quarter ending January 31, 2026 and fiscal year ending April 30, 2026, our strategic areas of focus, expectations and plans regarding our future ...

Core Insights - Elastic has been recognized as a Leader in the IDC MarketScape for Worldwide General-Purpose Knowledge Discovery 2025, highlighting its strong position in the market for search and analytics solutions [1][3]. Company Overview - Elastic is identified as the Search AI company, integrating search technology with artificial intelligence to transform data into actionable insights [8]. - The company has a significant user base, with over 50% of Fortune 500 companies utilizing its solutions [8]. Product Strengths - Elasticsearch is noted for its capabilities as a widely deployed open-source document and vector database, providing a powerful search and analytics engine essential for generative AI applications [1][2]. - The platform supports fast semantic and hybrid search, GPU-accelerated inference-as-a-service, and offers integrated observability and access controls [2][3]. Key Differentiators - Elastic's hybrid, semantic, and reranking models ensure AI systems are grounded in relevant and accurate context, a concept the company pioneered [5]. - The introduction of Agent Builder allows developers to create custom AI agents quickly, enhancing the platform's flexibility and usability [4][5]. - The company has achieved over 5.5 billion downloads of Elasticsearch, indicating a robust open-source community and developer engagement [5]. Strategic Vision - Elastic aims to help organizations unlock the full potential of their data by connecting content, context, and creativity through search and generative AI [5]. - The company emphasizes a unified data platform that combines search, observability, and security, helping organizations reduce costs and achieve faster insights [5]. Market Position - The IDC MarketScape assessment utilizes a rigorous scoring methodology to evaluate technology suppliers, providing a comprehensive overview of their competitive fitness [7]. - Elastic's recognition as a Leader reflects its strong capabilities and strategies in the knowledge discovery market [1][3].

Core Insights - Not all cash-generating companies are successful; some fail to reinvest effectively, limiting growth potential [1] - StockStory aims to identify companies with genuine upside potential [1] Companies to Sell - **Elastic (ESTC)** - Trailing 12-Month Free Cash Flow Margin: 20.2% [2] - Current stock price is $88.32, with a forward price-to-sales ratio of 5.3x [4] - **Edgewell Personal Care (EPC)** - Trailing 12-Month Free Cash Flow Margin: 1.9% [5] - Current stock price is $18.53, with a forward P/E ratio of 6.4x [7] Company to Watch - **Laureate Education (LAUR)** - Trailing 12-Month Free Cash Flow Margin: 15.6% [8] - Estimated sales growth of 12.5% for the next 12 months, indicating a slowdown from previous trends [8] - Operating margin increased by 7.7 percentage points over the last year [8] - Free cash flow margin expected to decrease by 2.4 percentage points in the coming year [8] Performance Concerns - **Laureate Education (LAUR)** - Organic revenue has underperformed over the past two years, suggesting a need for acquisitions to stimulate growth [9] - Earnings per share declined by 2.6% annually over the last three years, with flat revenue indicating reduced profitability per sale [9] - Free cash flow margin decreased by 4.9 percentage points over the last year due to increased investments [9] Positive Aspects - **Laureate Education (LAUR)** - Strong operating margin of 23.5% over the past two years due to disciplined cost controls [11] - Free cash flow generation is superior to most peers, enabling exploration of new investment opportunities [11] - Increasing returns on capital as previous investments begin to yield results [11]

Core Insights - Elastic has launched Agent Builder, a comprehensive set of capabilities that enables developers to create custom AI agents using company data in a matter of minutes [1] - Agent Builder offers an out-of-the-box conversational experience for exploring, analyzing, and optimizing data stored in Elasticsearch [1] - The evolution of AI agents is aimed at handling more complex and data-driven enterprise tasks, emphasizing the importance of reliability and accuracy [1] Company Developments - The introduction of Agent Builder signifies Elastic's commitment to enhancing developer tools and capabilities in the AI space [1] - The new features are designed to streamline the process of building AI agents, potentially increasing adoption among enterprises [1] Industry Trends - The demand for AI agents that can perform complex tasks is growing, indicating a shift towards more sophisticated data-driven solutions in the enterprise sector [1] - The focus on reliability and accuracy in AI applications reflects broader industry trends towards ensuring trust and effectiveness in AI technologies [1]

Core Insights - Elastic (NYSE:ESTC) has launched AutoOps for self-managed enterprise users at no additional cost, marking a significant development in its service offerings [1][3] - AutoOps is designed to enhance cluster management by providing cloud-connected services while ensuring that customer data remains within their self-managed environments [2][3] - The service offers real-time issue detection and resolution, simplifying cluster management through insights and automatic detection of operational issues [3] Company Overview - Elastic is a search AI company that provides software platforms for hybrid, public, or private clouds, as well as multi-cloud environments both in the US and internationally [4]

Summary of Elastic (NYSE:ESTC) Analyst Day - October 09, 2025 Company Overview - **Company**: Elastic (NYSE:ESTC) - **Event**: Financial Analyst Day - **Date**: October 09, 2025 - **Key Speaker**: Ash Kulkarni (CEO), Eric Prengel (Global VP of Elastic and Head of Investor Relations) Core Industry and Company Insights - **Industry**: Data management and analytics, focusing on unstructured data - **Company's Role**: Elastic is recognized as the world's most popular data platform for unstructured data, with over 5.5 billion downloads of its software, averaging over three downloads per second over 15 years [6][7][8] - **Competitive Advantage**: Elastic's ability to handle unstructured data is its greatest competitive advantage, with over 30 petabytes of new data ingested daily into paid clusters globally [7][9] Key Points and Arguments 1. **Unstructured Data Growth**: The company emphasizes the increasing importance of unstructured data, particularly in the context of AI and large language models (LLMs) [9][10] 2. **AI Integration**: Elastic's platform is positioned as a natural choice for AI applications due to its capabilities in managing unstructured data, which is crucial for training AI models [11][12] 3. **Product Announcements**: Six new product capabilities were announced, including: - **Agent Builder**: A tool for building AI agents directly on top of data [17] - **Elastic Inference Service**: A GPU-accelerated service for embedding and retrieval models [17] - **Acquisition of Jina AI**: Enhances Elastic's capabilities in multilingual and multimodal models [18] 4. **Customer Use Cases**: Notable customers include: - **DocuSign**: Chose Elastic for its intelligent agreement management platform, needing to search billions of documents [20] - **Legora**: An AI-native company that utilizes Elastic for legal research and drafting [21] - **National Health Service (NHS)**: Uses Elastic for patient record management, emphasizing data privacy and relevance [21] 5. **Observability and Security**: Elastic's observability platform is built to handle messy data, with over 90% of Elastic Cloud Observability customers using it for log analytics [28][30] 6. **Market Position**: Elastic is recognized as a leader in its field by analysts, with over 50% of Fortune 500 companies as customers, indicating significant growth potential [37] Additional Important Insights - **Context Engineering**: The concept of context engineering is highlighted as vital for AI applications, ensuring that LLMs have the right data and context to function effectively [55] - **Developer Community**: Elastic has a strong developer community, with 17% of professional developers and 19% of AI developers using Elasticsearch, showcasing its popularity and trust [56][57] - **Performance Improvements**: Recent enhancements include a new data lake architecture that maintains high performance while providing scalability and efficiency [47] Conclusion - **Future Outlook**: Elastic is well-positioned to capitalize on the growing demand for unstructured data management and AI integration, with a strong product lineup and a diverse customer base [39][38]

Core Insights - Elastic has launched the Elastic Inference Service (EIS), a GPU-accelerated inference-as-a-service designed for Elasticsearch semantic search, vector search, and generative AI workflows [1][2]. Group 1: Service Features - EIS provides an API-based inference service utilizing NVIDIA GPUs, integrated with Elasticsearch's vector database for low-latency and high-throughput inference [3]. - The first text-embedding model available on EIS is the Elastic Learned Sparse EncodeR (ELSER), with plans to support additional models for multilingual embeddings and reranking soon [3][5]. - EIS is designed to streamline the developer experience by eliminating model downloads, manual configuration, and resource provisioning, integrating directly with semantic text and the Inference API [7]. Group 2: Performance and Scalability - The service offers improved end-to-end semantic search capabilities, compatible with both sparse and dense vectors, as well as semantic reranking [7]. - GPU-accelerated inference provides consistent latency and up to 10x higher throughput for ingestion compared to CPU-based alternatives [7]. - EIS is available on Serverless and Elastic Cloud Hosted deployments, accessible across all cloud service providers and regions [5]. Group 3: Pricing and Support - EIS features consumption-based pricing, charged per model per million tokens, making it easy for users to get started and access support [7]. - Elastic provides intellectual property indemnity for all models offered on EIS, ensuring peace of mind for users [7].

Core Insights - Elastic has been recognized as a leader in The Forrester Wave™ Cognitive Search Platforms, Q4 2025 report, highlighting its strong position in the market [1] - Elasticsearch achieved the highest possible scores in eight criteria, including relevancy, showcasing its effectiveness and reliability [1] - The platform is noted for its capabilities in handling both structured and unstructured data, making it suitable for generative AI applications [1] Company Overview - Elastic is identified as the "Search AI Company," emphasizing its focus on search and analytics solutions [1] - Elasticsearch is described as a widely deployed open-source document and vector database, indicating its broad adoption and versatility [1] - The platform provides developers with a powerful search and analytics engine, essential for modern application needs [1]

Core Insights - Elastic N.V. is leveraging AI software products to help businesses manage and extract value from their data, with increasing demand driving revenue growth [2][3] - The stock is currently 54% below its 2021 peak, but analysts are generally optimistic, with a majority recommending a buy [3][12] Company Overview - Elastic has developed Elasticsearch, a tool that allows employees to perform natural language searches on internal data, improving efficiency in information retrieval [5] - The company introduced Search AI, enhancing user experience by integrating generative AI into Elasticsearch, which improves response quality and speed [6] Market Context - The International Data Corporation reports that approximately 480 exabytes of new data are generated daily, highlighting the challenges businesses face in data management [4] - The AI sector is rapidly expanding, with significant opportunities for companies like Elastic to provide productivity-enhancing tools [15] Financial Performance - In Q1 of fiscal 2026, Elastic reported $415 million in revenue, a 20% increase year-over-year, surpassing management's forecast [8] - The company had 1,550 customers with annual contracts exceeding $100,000, indicating strong demand from large organizations [9] - Operating expenses increased by only 13% year-over-year, leading to a reduced net loss of $24.6 million compared to $49.2 million in the previous year [10] - On a non-GAAP basis, Elastic achieved profitability of $64.8 million, a 74% increase from the prior year [11] Analyst Sentiment - Among 30 analysts covering Elastic, 19 have a buy rating, with an average price target of $119.91, suggesting a potential upside of 42% [12] - The highest target of $150 indicates a possible 77% increase, reflecting confidence in the company's growth trajectory [12][13] Valuation Insights - Elastic's price-to-sales (P/S) ratio has decreased from nearly 30 in 2021 to 5.7, making it more attractively valued compared to its historical levels [13] - The long-term growth potential in the AI software market, estimated at $13 trillion by 2030, supports the bullish outlook for Elastic [15]