Elastic has expanded its collaboration with OpenAI to help organizations build production-ready AI applications and agents by combining OpenAI’s reasoning models as well as the enterprise search, retrieval, and governance capability of Elasticsearch. The collaboration seeks to overcome the problem that has long faced enterprises in using AI; that of making available to AI agents secure access to the right information, most of which exists in unstructured form in the organization in documents, logs, tickets, metrics, traces, and security alerts. The Elasticsearch system acts as the retrieval layer for integrating lexical and vector search, semantic reranking, filters, and access controls into one system. In doing so, AI agents gain access to the real-time permission-aware enterprise context without having to make unnecessary data transmissions and minimizing token costs.
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“The success of enterprise AI depends on connecting powerful models with the knowledge businesses already possess,” said Greg Tademoto, global vice president, Business Development & Strategic AI Partnerships at Elastic. “Much of that knowledge is buried in unstructured data. By combining OpenAI’s advanced reasoning with Elasticsearch’s retrieval and governance capabilities, we’re helping enterprises build AI agents that are accurate, secure and useful in production.” “Great AI needs great context. We’re excited to collaborate with Elastic to bring OpenAI’s 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,” said Colleen Kapase, vice president, Strategic Global Partnerships & Ecosystems at OpenAI.