Red Hat & Elastic extend partnership for enhanced AI search experiences

Red Hat and Elastic have announced the extension of their collaboration to bring about next-generation search experiences. These new experiences will be supported by retrieval augmented generation (RAG) patterns, using Elasticsearch as the key vector database solution. The solution will be integrated into the Red Hat OpenShift AI platform, equipping enterprises with the tools required to deliver, manage and refine RAG solutions on a uniform platform.

Elastic's collaboration with Red Hat highlights their joint aim of accelerating developers' use of vector databases. Elasticsearch forms an essential part of Elastic's enterprise customers' key business applications that demand high performance at scale. This makes it a natural fit to pair with Red Hat's OpenShift AI. As firms face increasing demands for the integration of AI solutions and risk reduction, RAG plays a crucial role in introducing large language models (LLMs) to business applications.

RAG empowers IT teams to utilise the advantages of LLMs combined with private data stores. This conjunction enables the training of models with specific, private data without altering the foundational model. Efficient search retrieval is vital in this aspect, as using private repositories on a large scale to provide LLMs with the correct information can prove costly. Role-based controls in retrieval help maintain protection for sensitive data while it's being used for training general-purpose LLMs.

Both Red Hat OpenShift AI and Elasticsearch offer vital support to companies wanting to leverage RAG's full potential. Red Hat OpenShift AI provides a dependable MLOps platform to automate, deploy, and monitor models on a large scale. Meanwhile, Elasticsearch delivers robust hybrid search solutions for scaling and drawing AI responses, with superior search and security features to make the results more user-friendly.

Moreover, Red Hat's Elasticsearch Relevance EngineTM (ESRETM) facilitates developers' construction of cutting-edge search with proprietary enterprise data, thus paving the way for semantic search and RAG applications using various third-party machine learning (ML) models. The cohesion of Red Hat OpenShift AI with Elasticsearch allows for more profound and comprehensive customer support, fostering more innovation and integration with Red Hat's vast ecosystem of AI partners.

This enhanced collaboration between Red Hat and Elastic demonstrates the positive impact that AI can have on business applications and the wider market. By facilitating enterprises at various stages of their AI adoption, Red Hat aids them in capitalising on their often-underutilised data, creating a significant differentiator for organisations.

Steven Huels, Vice President and General Manager of the AI Business Unit at Red Hat, stated: "Broadening our partner ecosystem through our collaboration with Elastic strengthens users' power of choice on a reliable, consistent AI platform."

Matt Riley, General Manager of Search at Elastic, shared a similar sentiment: "Red Hat's hybrid MLOps and GenAI application development lifecycle tools will enable Elasticsearch developers to build RAG and AI-enabled search applications more easily."