Elastic launches AI ecosystem for faster RAG app development
Elastic has announced the introduction of its AI Ecosystem, designed to aid enterprise developers in the accelerated construction and deployment of Retrieval Augmented Generation (RAG) applications.
The Elastic AI Ecosystem offers a curated set of AI tools integrated with the Elasticsearch vector database aimed at reducing time-to-market and enhancing return on investment (ROI) for developers. Stephen O'Grady, Principal Analyst with RedMonk, stated, "The enterprise AI market is evolving at an accelerating rate, with new products and services arriving daily. While this dizzying array of options expands the portfolio of capabilities available to enterprises and their developers, it can simultaneously slow them down by increasing the number of choices and integrations that need to be made." He added, "One way to balance the need for new capabilities with a streamlined developer experience is by thoughtfully curating and integrating tools to maximise their collective capabilities. This is what Elastic designed its AI Ecosystem to do."
The ecosystem provides pre-built Elasticsearch integrations, enhancing ease of access to AI models, cloud infrastructure, and various operational frameworks. This serves to optimise the developer workflow by enabling the delivery of relevant experiences through RAG, data preparation from multiple sources, model evaluation, utilisation of GenAI frameworks, and secure AI application deployment.
Elastic's platform includes integration with several prominent AI technology providers, such as Alibaba Cloud, Amazon Web Services, and Google Cloud, among others. Steve Kearns, General Manager of Search at Elastic, commented, "Elasticsearch is the most widely downloaded vector database in the market, and customers and developers want to use it with the ecosystem's best models, platforms, and frameworks to build compelling RAG applications. With our handpicked ecosystem of technology providers, we're making it easier for developers to leverage Elastic's vector database and choose the best combination of leading-edge technologies for their RAG applications. These integrations will help developers test, iterate, and deliver their RAG applications to production faster and improve the accuracy of their Gen AI applications."
Stephen Orban, Vice President, Migrations, ISVs, & Marketplace at Google Cloud, reflected on the collaboration with Elastic stating, "We're committed to making it easy for developers to build and deploy generative AI applications. Through our partnership with Elastic, enterprises and developers gain access to powerful resources, streamlined frameworks, and robust governance tools—all powered by Google Cloud's AI-optimised infrastructure to deliver next-gen AI capabilities."
Jeff Boudier, Head of Product at Hugging Face, noted, "Combining Hugging Face's Inference Endpoints with Elastic's retrieval relevance tools helps users gain better insights and improve search functionality. With this integration, developers get a complete solution to leverage the best open models, hosted on Hugging Face multi-cloud GPU infrastructure, to build semantic search experiences in Elasticsearch."
LangChain CEO, Harrison Chase, highlighted the benefits, saying, "Our work with Elastic helps developers build GenAI applications faster and more effectively. Leveraging LangGraph alongside Elasticsearch's vector database, developers can create high-impact agentic applications that streamline the path from development to production."
Liliana Gonzalez, Senior Director, Partner Development at Microsoft, added, "Elastic's integrations with Microsoft Azure AI solutions enable their users to use cutting-edge technology to build production-ready, AI applications for their customers. This dynamic collaboration is a powerhouse of continuous innovation, driving benefits for customers, Elastic, Microsoft, and the broader partner ecosystem."
Further emphasising the strategic partnerships, Steven Huels, Vice President and General Manager, AI Engineering at Red Hat, said, "Broadening our collaboration with Elastic strengthens users' power of choice on a reliable, consistent AI platform. We're pleased to bring new support for RAG patterns, a critical first step for enterprises beginning their AI journeys and building trust within the AI marketplace."
