May 23, 2023

Elastic to power generative AI models with Elasticsearch Relevance Engine SHARE Enterprise search technology provider Elastic N.V. is aiming to help companies build and integrate generative artificial intelligence models powered by their own corporate data with the launch of its new Elasticsearch Relevance Engine today. ESRE, as the new tool is called, is powered by built-in vector search and transformer models that combine the latest innovations in generative AI to proprietary enterprise data. Elastic is the creator of the popular open-source Elasticsearch platform , which enterprises use to store, search and analyze huge volumes of structured and unstructured data in close to real time. Elasticsearch serves as the underlying engine for millions of applications that have more complex features and requirements. With the launch of ESRE, Elasticsearch will soon power a new generation of generative AI applications built on enterprise data. ESRE will enable companies to build highly specialized models trained on their own proprietary data, both structured and unstructured, the company said. “Generative AI is a revolutionary moment in technology and the companies that get it right, fast, are tomorrow’s leaders,” said Elastic Chief Executive Ash Kulkarni. “The Elasticsearch Relevance Engine is available today, and we’ve already done the hard work of making it easier for companies to do generative AI right.” Elastic said ESRE is effectively democratizing access to AI and machine learning. It provides unified application programming interfaces for vector search, BM25f search and hybrid search capabilities, and combines them with a new transformer model that’s small enough to fit inside a regular business laptop. Users will be able to build custom generative AI applications that leverage their unique, proprietary datasets, without worrying over the size or cost of training and running large language models, Elastic said. Companies will also have the ability to bring their own transformer models and integrate with third-party models, such as OpenAI LP’s ChatGPT, to create secure chat models that leverage their own, very specific data. Elastic said ESRE is already being used by some of its most prominent customers to augment their internally built generative AI applications. They include Relativity ODA LLC , a provider of legal technology, which is using ESRE and Microsoft Corp.’s Azure OpenAI Service to improve the relevance of results within its eDiscovery product RelativityOne. Relativity Chief Product Officer Chris Brown said ESRE has enabled it to build “industry-leading search capabilities” that help its customers and partners better organize their data and act on it. “We’re experimenting with ESRE right now and are excited about its potential to deliver powerful, AI-augmented search results to our customers,” he said. James Governor, co-founder of the developer-focused analyst firm RedMonk, said though enterprises are excited about the potential of generative AI, they’re also swamped by the pace of innovation. “ESRE is designed to ease adoption of transformers, homemade and third-party LLM models, building on the original core strengths of Elastic in search,” he explained. Image: Elastic A message from John Furrier, co-founder of SiliconANGLE: Your vote of support is important to us and it helps us keep the content FREE. One-click below supports our mission to provide free, deep and relevant content.