Big moment for Postgres!AI agents broke the idea of what a database is supposed to do.Traditional databases were built for humans, and Agents broke that model.- They branch endlessly.- They run ten experiments at once.- They need isolation, context, memory, structured reasoning, and safe sandboxes.Letting agents touch production systems is terrifying because the old model of Postgres was never built for this kind of behavior.Agentic Postgres is an agent-ready version of Postgres by @TimescaleDB that solves ...

Core Insights - Elastic NV's stock surged by 8% in after-hours trading following significant announcements, rising to $88.07 from $81.55 [1] Group 1: Acquisition of Jina AI - Elastic has completed the acquisition of Jina AI, a company specializing in open-source tools for handling diverse data types and languages [2] - This acquisition enhances Elastic's capabilities in vector search, retrieval-augmented generation (RAG), and context engineering for agentic AI, incorporating dense vector models for text and image processing [3] - The former CEO of Jina AI, Han Xiao, has joined Elastic as vice-president of AI, emphasizing the importance of search in generative AI [4] Group 2: Introduction of GPU-Accelerated Inference Service - Elastic launched the Elastic Inference Service (EIS), utilizing NVIDIA GPUs to achieve up to 10x faster data processing compared to CPU-based options [5] - The EIS offers an API-based inference service and features consumption-based pricing per million tokens, available on Serverless and Elastic Cloud Hosted deployments [6] Group 3: Stock Buyback Program - The board of Elastic has authorized a share repurchase program of up to $500 million with no expiration date, reflecting management's confidence in the company's business strength [7] - Over the past year, Elastic's stock has increased by 2.10%, although it has decreased by 17.69% in 2025, with a market capitalization of $8.67 billion [7]

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]