Elastic's shares jumped after the company announced Jina On-Prem, allowing businesses to deploy its Jina AI models in secure on-premises and air-gapped environments. The initiative targets organisations in regulated industries that must keep data in-house for security or regulatory compliance. The new offering provides enterprise-grade data extraction and semantic search capabilities without requiring internet connectivity or third-party AI services. By giving companies full control over their data, costs, and performance, Elastic aims to enhance services for clients requiring secure and independent data management systems. Elastic's shares closed at $61.21, up 3.6% from the previous close. The stock remains down 15.6% year-to-date and is trading 35.2% below its 52-week high of $94.47 from November 2024.

Elastic brings jina multimodal and multilingual semantic search to on-premises and air-gapped environments. July 27, 2026 Jina embedding and reranker models with frontier-grade accuracy are now available with zero external calls SAN FRANCISCO-(BUSINESS WIRE)- Elastic (NYSE: ESTC), the Search AI Company, today announced that Jina AI models are available for on-premises and air-gapped environments through Jina On-Prem. Designed for regulated industries, air-gapped environments, or organizations that want full control over data, cost, and performance, Jina On-Prem delivers enterprise-grade data extraction and semantic search with no internet connection or third-party AI services required. Many organizations need AI systems that don't depend on a live connection to a third-party service. While self-hosted alternatives exist, they come with tradeoffs. Supporting multiple media types and languages typically requires assembling separate models, and licensed platforms cleared for air-gapped deployments are largely constrained to text and images. The most accurate open-source models also carry substantial compute requirements, meaning comprehensive coverage often demands running several large models simultaneously. Jina On-Prem packages Jina AI's family of models that cover text, images, audio, and video in a single embedding space so they can now run entirely within a customer's own environment, making no calls to the outside once deployed. Data stays on-premises, and teams retain full control over cost, model access, and performance. Small Jina models run on a single 8GB GPU, at a fraction of the cost, while matching the accuracy of far larger models that need many times more GPU memory. "Historically, teams running search and retrieval in regulated or disconnected environments have had to choose between capability and control," said Ajay Nair, general manager, Elasticsearch and Platform, Elastic. "The ability to run Jina models fully on-premises removes that compromise by giving them Jina AI's high-performance reader, embedding and reranking models directly in their own environments, allowing them to build AI applications without depending on external AI services." Jina On-Prem installs with a single command and makes no outbound network calls once deployed: no license server, no telemetry or logging endpoint, and no connection to a model registry. The suite includes all 28 Jina AI models, including the jina-embeddings-v5-omni multimodal embedding model and jina-reranker-v3, and supports both CPU and GPU hardware with automatic GPU detection. Applications can reach it through standard API schemas so existing integrations work without rewriting code. Jina On-Prem also serves as a drop-in replacement for models served through Elastic Inference Service (EIS), so air-gapped Elastic deployments can integrate it directly without changing how applications call their embedding and reranking models. Availability Jina On-Prem is available now for download via GitHub through an access token. Installation instructions are available on the Jina On-Prem Quick Start page, with a separate bundling guide for teams composing their own Docker container. To license Jina On-Prem, please contact Elastic Sales. Additional Materials About Elastic Elastic (NYSE: ESTC), the Search AI Company, integrates its deep expertise in search technology with artificial intelligence to help everyone transform all of their data into answers, actions, and outcomes. Elastic's Search AI Platform - the foundation for its search, observability, and security solutions - is used by thousands of companies, including more than 50% of the Fortune 500. Learn more at elastic.co. Elastic and associated marks are trademarks or registered trademarks of elasticsearch B.V. and its subsidiaries. All other company and product names may be trademarks of their respective owners.

Elastic and Deductive AI join forces to accelerate agentic incident investigation for engineering teams. July 22, 2026 Today, Elastic announced that it has entered into an agreement to acquire Deductive AI, an AI-powered investigation platform that helps engineering teams identify and resolve production issues faster. As modern applications become more distributed, interconnected, and complex, teams have more telemetry than ever before and engineers are spending too much time piecing together information across tools to understand what happened, why it happened, and what to do next. Deductive AI was built to address that challenge. Deductive AI has built an AI SRE agent that connects to a customer's code, telemetry sources, and organizational knowledge to help engineering teams investigate alerts and production issues. The agent conducts root cause analysis by gathering evidence, forming and testing hypotheses, and reasoning across multiple sources of context to help teams understand what happened, why it happened, and what should happen next. Every investigation also becomes a learning opportunity, with successful investigation paths continuously refined and reused to improve future investigations. The acquisition accelerates its goal to bring more AI-powered investigation and automation to Elastic Observability. By combining Elastic's existing AI capabilities to infer meaningful entities, relationships, and significant operational events from telemetry with Deductive AI's knowledge graph and investigation engine, Elastic will help users identify root cause faster, reduce time spent on manual investigation, and resolve production issues more efficiently. Existing Deductive AI customers will continue to receive support while integration plans are developed. Elastic look forward to sharing more details about its product roadmap in the coming months. Elastic asked Rakesh Kothari, CEO and cofounder of Deductive AI, to share some words on what it means to join Elastic: "From the beginning, our goal was to help engineering teams accelerate root cause analysis and incident investigation, so they could focus on what truly drives impact: building and shipping great products. Joining Elastic allows us to bring that vision to more customers at a far greater scale and accelerate the development of AI-powered investigation capabilities. We couldn't be more excited about what's ahead." I'm delighted to welcome cofounders Rakesh and Sameer to Elastic along with the rest of the Deductive AI team, and Elastic look forward to building the future of AI-powered observability together.