{"id":987207,"date":"2026-07-30T08:15:04","date_gmt":"2026-07-30T12:15:04","guid":{"rendered":"https:\/\/www.marketnewsdesk.com\/index.php\/elastic-and-openai-collaborate-to-bring-frontier-intelligence-to-unstructured-enterprise-data\/"},"modified":"2026-07-30T08:15:04","modified_gmt":"2026-07-30T12:15:04","slug":"elastic-and-openai-collaborate-to-bring-frontier-intelligence-to-unstructured-enterprise-data","status":"publish","type":"post","link":"https:\/\/www.marketnewsdesk.com\/index.php\/elastic-and-openai-collaborate-to-bring-frontier-intelligence-to-unstructured-enterprise-data\/","title":{"rendered":"Elastic and OpenAI Collaborate to Bring Frontier Intelligence to Unstructured Enterprise Data"},"content":{"rendered":"

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Elastic and OpenAI Collaborate to Bring Frontier Intelligence to Unstructured Enterprise Data<\/b><\/p>\n

Collaboration combines OpenAI\u2019s advanced reasoning models with governed enterprise context in Elasticsearch across AI applications, security operations, and observability<\/i><\/p>\n

SAN FRANCISCO–(BUSINESS WIRE<\/a>)–Elastic<\/a> (NYSE: ESTC), the Search AI Company, today announced an expanded collaboration with OpenAI to help organizations build production-ready AI applications and agents using OpenAI models with Elasticsearch. By combining Elasticsearch’s retrieval, search and governance capabilities with OpenAI’s advanced reasoning models, organizations can ground AI in their own enterprise data to enable more accurate, secure and reliable AI at scale.<\/p>\n

AI agents are only as useful as the enterprise context they can access. Yet most of that information remains out of reach. According to Gartner\u00ae, \u201cunstructured data, such as documents and multimedia files, accounts for 70% to 90%<\/a> of organizational data.\u201d1<\/sup> That context is spread across documents, tickets, logs, metrics, traces, and security alerts, changes continuously, and is governed by different permissions. Without access to the right enterprise context, even advanced AI models struggle to deliver accurate, reliable results.<\/p>\n

Elasticsearch provides the retrieval layer, combining lexical and vector search, semantic reranking, filtering, and access controls in a single platform. It helps agents find relevant, real-time context with the right permissions, reducing unnecessary data sent to the model and improving retrieval quality, all with lower token costs. Together with OpenAI models, developers can build reliable, cost-efficient AI agents for critical enterprise workflows.<\/p>\n

\u201cThe success of enterprise AI depends on connecting powerful models with the knowledge businesses already possess,\u201d said Greg Tademoto, global vice president, Business Development & Strategic AI Partnerships at Elastic.<\/b> \u201cMuch of that knowledge is buried in unstructured data. By combining OpenAI\u2019s advanced reasoning with Elasticsearch’s retrieval and governance capabilities, we\u2019re helping enterprises build AI agents that are accurate, secure and useful in production.\u201d<\/p>\n

\u201cGreat AI needs great context. We\u2019re excited to collaborate with Elastic to bring OpenAI\u2019s models closer to the data businesses rely on – helping them build AI agents that are more accurate, more secure, and ready to deliver real-world results,\u201d said Colleen Kapase, vice president, Strategic Global Partnerships & Ecosystems at OpenAI.<\/b><\/p>\n

Elastic and OpenAI will focus on delivering three customer outcomes:<\/p>\n