Coquitlam, BC – TheNewswire - October 9, 2025 – Fuse Battery Metals Inc. (“the Company“ or “Fuse”) (TSXV: FUSE, OTCQB: FUSEF FRA:43W3) is pleased to announce that effective today, it has appointed Andrew Gertler as a Director of the Company.   Andrew Gertler brings a wealth of insight to his role as a board director, drawing on a 40-year career in business with a specialized focus on alternative investments, including real estate and distressed debt.  His expertise was honed through leadership positions a ...

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Core Viewpoint - Elastic has announced a share repurchase program authorized for up to $500 million of its outstanding ordinary shares, reflecting confidence in its business and strategy [1] Summary by Category Company Actions - The Board of Directors of Elastic has approved a share repurchase program [1] - The program allows for the repurchase of up to $500 million of the company's shares [1] - There is no expiration date for the share repurchase program [1] Management Perspective - The share repurchase program indicates the Board and management team's confidence in the strength of Elastic's business, strategy, and execution [1]

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]

Business Overview and Growth - Elasticsearch is the world's most popular open-source data platform for unstructured data, evidenced by 55 billion downloads and ranking as the 1 search engine and VectorDB[10, 11] - Elastic's total revenue has grown consistently, reaching $1483 million in FY25, with a year-over-year growth of 17%[16] - The company is targeting a $296 billion total addressable market (TAM) by 2029, driven by Search, Security, Observability, and GenAI[52] AI and Technology - Elastic has a strong foundation for AI, with 15 years of development in native vector search and AI workloads[22, 23] - The Elasticsearch platform ingests 30 petabytes of raw data per day and handles 30 billion queries per day on Elastic Cloud[13] - Elastic Cloud has over 2200 customers using AI[32] Customer Adoption and Expansion - Elastic has over 21550 total customers, with over 1550 customers spending more than $100K ACV[56] - 50% of Fortune 500 companies are paid customers of Elastic[56] - 90% of Elastic Cloud observability customers use log analytics, and 35% use beyond log analytics[38] - 95% of Elastic Cloud security customers use Elastic as a SIEM, and 20% use it beyond SIEM for use cases like XDR[45] Financial Performance and Targets - Elastic aims for a medium-term sales-led subscription revenue growth of 20%, comprising 15% base growth and 5% GenAI tailwinds[265, 267] - The company is targeting a non-GAAP operating margin of over 20% and an adjusted free cash flow margin of over 20% in the medium term[267] - Elastic's adjusted free cash flow reached $286 million in FY25, representing a 19% margin[271]

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 Viewpoint - Confluent is exploring a potential sale after attracting interest from private equity firms and technology companies, leading to a significant rally in its stock price [1][5]. Company Overview - Confluent is a data streaming technology company that integrates AI and data analytics, primarily serving as a backend application provider [2][3]. - The company has faced challenges, including a 38% decline in stock price over the last three years and an 18.5% drop year-to-date [3]. Financial Performance - Confluent reported a significant operating loss of approximately $1.3 billion on sales of around $1 billion last year, with no profits recorded in the past decade [6]. - The company has high R&D and selling, general, and administrative (SG&A) expenses, which contribute to its financial struggles [6][9]. - Despite these challenges, Confluent holds about $1.95 billion in cash, representing approximately 27% of its market capitalization of around $7.2 billion [10]. Market Dynamics - The competitive landscape includes major players like Snowflake, DataDog, Elastic, and MongoDB, which poses challenges for Confluent in terms of scalability and customer base [9][13]. - The recent loss of a significant AI-native customer led to a 30% drop in stock price, highlighting the volatility and risks associated with customer retention [4][13]. Investment Interest - The announcement of exploring a sale has sparked interest from institutional investors and private equity, indicating potential for operational streamlining and cost-cutting [5][11]. - The current environment suggests a trend towards consolidation within the data infrastructure sector, making Confluent's situation noteworthy [8][12].

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 has been recognized as a Leader in the IDC MarketScape for Worldwide Extended Detection and Response (XDR) Software 2025 Vendor Assessment, highlighting its strong position in the market [1] Company Overview - Elastic is identified as the "Search AI company," emphasizing its foundational strength in search technology [1] - The company has unified Security Information and Event Management (SIEM), XDR, and cloud security capabilities into a single platform, enhancing its competitive edge [1] Market Position - The recognition from IDC indicates that Elastic's differentiation in the XDR market is largely due to its robust search capabilities [1] - Chris Kissel, research vice president at IDC, noted the importance of Elastic's integrated approach in the evolving security landscape [1]