Elastic, the company behind Elasticsearch®, announced the Elasticsearch open inference API supports Cohere’s Rerank 3 model.
As the first vector database to support Cohere Rerank 3, Elasticsearch now enables developers to benefit from greater semantic relevance to keyword and vector search retrieval for prompting large language models (LLMs).
“The combination of the Elasticsearch open inference API and Cohere Rerank 3 gives developers stronger ‘top n’ results, without requiring any changes to the model or data indexes – which are both expensive operations – providing better search results to ground LLMs,” said Shay Banon, founder and chief technology officer at Elastic. “As part of our ongoing partnership with Cohere, we’ve already made it easy for Elasticsearch developers to use Cohere’s embeddings. Adding Cohere’s incredible reranking capabilities to refine results past the first stage of retrieval was a natural evolution to our partnership.”
With this first-of-its-kind integration available today, developers with data stored in existing Elasticsearch indexes benefit from Cohere’s enhanced last-stage reranking capabilities. Users can also leverage the Elasticsearch vector database and hybrid search capabilities for embeddings from other third-party models with Cohere Rerank 3.
“We continue to be impressed by the speed of innovation from Elasticsearch. They offer powerful search and retrieval capabilities and are leading the way with investments into their vector database and hybrid search offerings,” said Jaron Waldman, chief product officer at Cohere. “We are excited to deepen our partnership by enabling developers to use Elasticsearch with Cohere’s state-of-the-art Rerank 3 model from day one.”
Support for Cohere’s Rerank 3 model is available today.
The Latest
64% of enterprise networking teams use internally developed software or scripts for network automation, but 61% of those teams spend six or more hours per week debugging and maintaining them, according to From Scripts to Platforms: Why Homegrown Tools Dominate Network Automation and How Vendors Can Help, my latest EMA report ...
Cloud computing has transformed how we build and scale software, but it has also quietly introduced one of the most persistent challenges in modern IT: cost visibility and control ... So why, after more than a decade of cloud adoption, are cloud costs still spiraling out of control? The answer lies not in tooling but in culture ...
CEOs are committed to advancing AI solutions across their organization even as they face challenges from accelerating technology adoption, according to the IBM CEO Study. The survey revealed that executive respondents expect the growth rate of AI investments to more than double in the next two years, and 61% confirm they are actively adopting AI agents today and preparing to implement them at scale ...
A major architectural shift is underway across enterprise networks, according to a new global study from Cisco. As AI assistants, agents, and data-driven workloads reshape how work gets done, they're creating faster, more dynamic, more latency-sensitive, and more complex network traffic. Combined with the ubiquity of connected devices, 24/7 uptime demands, and intensifying security threats, these shifts are driving infrastructure to adapt and evolve ...
The development of banking apps was supposed to provide users with convenience, control and piece of mind. However, for thousands of Halifax customers recently, a major mobile outage caused the exact opposite, leaving customers unable to check balances, or pay bills, sparking widespread frustration. This wasn't an isolated incident ... So why are these failures still happening? ...
Cyber threats are growing more sophisticated every day, and at their forefront are zero-day vulnerabilities. These elusive security gaps are exploited before a fix becomes available, making them among the most dangerous threats in today's digital landscape ... This guide will explore what these vulnerabilities are, how they work, why they pose such a significant threat, and how modern organizations can stay protected ...
The prevention of data center outages continues to be a strategic priority for data center owners and operators. Infrastructure equipment has improved, but the complexity of modern architectures and evolving external threats presents new risks that operators must actively manage, according to the Data Center Outage Analysis 2025 from Uptime Institute ...
As observability engineers, we navigate a sea of telemetry daily. We instrument our applications, configure collectors, and build dashboards, all in pursuit of understanding our complex distributed systems. Yet, amidst this flood of data, a critical question often remains unspoken, or at best, answered by gut feeling: "Is our telemetry actually good?" ... We're inviting you to participate in shaping a foundational element for better observability: the Instrumentation Score ...
We're inching ever closer toward a long-held goal: technology infrastructure that is so automated that it can protect itself. But as IT leaders aggressively employ automation across our enterprises, we need to continuously reassess what AI is ready to manage autonomously and what can not yet be trusted to algorithms ...
Much like a traditional factory turns raw materials into finished products, the AI factory turns vast datasets into actionable business outcomes through advanced models, inferences, and automation. From the earliest data inputs to the final token output, this process must be reliable, repeatable, and scalable. That requires industrializing the way AI is developed, deployed, and managed ...