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RERANK

Refine your enterprise search and retrieval with precise result ranking

Rerank passes only the most relevant documents into your RAG pipeline and agentic workflows — reducing token use, minimizing latency, and boosting accuracy.

Request a demo
Read the documentation
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Rerank logo and text centered on a purple abstract background with smooth, rounded shapes.

Trusted by industry leaders and developers worldwide

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The precision filter at the end of your retrieval pipeline

From improving response quality to feeding AI agents higher-signal inputs, Rerank delivers accurate retrieval ranking at enterprise scale.

  • AI Agents
  • RAG Accuracy
  • Upgraded Search

Support intelligent agents

Guide AI agents with leaner, more relevant context — minimizing trace bloat and improving task execution.

AI Agents UI
AI Agents UI

Learn more about Rerank

Image for Context

Cohere Team - Dec 02, 2024

Introducing Rerank 3.5: Precise AI Search

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Cohere Team - Jul 24, 2024

Introducing Rerank 3 on Microsoft Azure AI

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Sylvie Shi, Chris Kim - Jul 05, 2023

How to Boost Wikipedia Search with Rerank

Read more

Designed for the realities of enterprise retrieval

Rerank adapts to the messiness of real-world queries and data — prioritizing the most relevant results with speed and accuracy.

Request a demo
Read the documentation

Applies cross-attention for fine-grained ranking

Compare query and document directly — improving result quality for complex, under-specified queries.

Applies cross-attention for 
fine-grained ranking section graphic
Applies cross-attention for 
fine-grained ranking section graphic

Fluent in 100+ global business languages

Surface relevant results across language boundaries with accurate retrieval from international and multilingual datasets.

Fluent in 100+ global business languages section graphic
Fluent in 100+ global business languages section graphic

Compatible with complex enterprise data

Rank multi-aspect and semi-structured docs — like emails, tables, JSON, and code — with the same precision as long-form text.

Compatible with complex enterprise data section graphic
Compatible with complex enterprise data section graphic

Secure. Scalable. Seamless.

  • Privately deployable: Deploy Rerank in your virtual private cloud (VPC) or on-premises environment for full control over data privacy and security. Also available through Cohere’s platform or trusted cloud providers.
  • Built for speed and scale: Reorder retrieved results in real time with high accuracy and minimal latency — reducing compute costs in RAG systems by passing fewer, more relevant documents to your generative model.
  • Easy to integrate: Add precision to existing search pipelines with just a few lines of code — no heavy setup or system changes required.

Enhancing retrieval in workplace solutions

See how Rerank adds precision to our workplace AI tools — North and Compass.

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North

Powered by Command A, Compass, Embed, and Rerank, North helps you transform the way you work with secure AI agents, advanced search, and leading generative AI - all in one place.

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Compass

Unlock the potential of your data with an intelligent search and discovery system that doesn't compromise on security.

Learn more

Deployed and delivering — See what global teams are saying about Rerank

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La force motrice de la solution d’expérience de travail numérique d’Atomicwork est le modèle Rerank de Cohere et Azure AI Studio, qui alimente Atom AI, notre assistant numérique, avec la précision et la performance nécessaires pour livrer des résultats dans le monde réel.

En savoir plus
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Logo de Atomicwork

La force motrice de la solution d’expérience de travail numérique d’Atomicwork est le modèle Rerank de Cohere et Azure AI Studio, qui alimente Atom AI, notre assistant numérique, avec la précision et la performance nécessaires pour livrer des résultats dans le monde réel.

En savoir plus
Image vedette d’Atomicwork : des hommes et femmes d’affaires marchant dans un grand centre de congrès aux lumières vives.

Ready to refine your retrieval pipeline?

Talk to our team to learn how Rerank can help you improve result quality, reduce system load, and scale semantic retrieval into production.

  • Evaluate how Rerank can improve accuracy and efficiency across your existing retrieval stack
  • Explore how Rerank, Embed, and Command can work together in RAG and agentic pipelines
  • Determine the best deployment model for your infrastructure and privacy requirements
  • Get help adding Rerank to your stack — no major setup or system changes needed