Cohere
提供私有、安全且可定制的企业级人工智能平台与模型产品。
公司概览
- 公司类型
- 企业应用与交付
目标客户 · CoreWeave / Ada / Draftwise / BambooHR / Oracle / Atomicwork
产品与交付
North
面向企业的智能代理(agentic)AI平台,具备安全性、智能性、成本效益与自主控制能力。
Model Vault
专用模型推理平台,提供端到端加密、完全隔离的高性能推理,兼具SaaS便捷性。
Aya Models
大规模多语言AI模型。
落地案例
Integrating Cohere into Draftwise boosted the quality of search results by 30%
- 披露结果
- 集成Cohere后搜索结果质量提升了30%。
How CoreWeave used Cohere North to transform its customer support in 90 days
- 披露结果
- 使用Cohere North在90天内转型客户支持业务。
AI agent retrieval: How Ada scales with Cohere
Ada的AI Agent在生成正确回答前必须检索到正确信息;如果检索缓慢或错误,会导致Agent响应缓慢且生成错误答案,在线交互中毫秒级延迟至关重要。
- 流程与架构
- 在Amazon SageMaker AI上部署Cohere Embed,并使用Cohere Model Vault进行离线嵌入推理。
- 披露结果
- 通过在Amazon SageMaker AI上使用Cohere Embed,实现77毫秒中位延迟和90.7%的top-10召回率;通过Cohere Model Vault使离线嵌入性价比吞吐量提升2.7倍;向量存储需求减少4倍且检索性能未出现可衡量的下降。
AI agent retrieval: How Ada scales with Cohere
在在线语音场景中对延迟预算的要求比此前检索方案所能稳定提供的更严格,需要同时满足质量、低延迟以及跨区域多租户扩展性三项要求,且单一架构无法同时高效兼顾离线与在线两类工作负载。
- 流程与架构
- 离线知识库索引采用 Cohere 托管的 Cohere Model Vault 运行模型并支持批量嵌入;在线检索路径则在专用 Amazon SageMaker AI 实例上自托管 Cohere Embed,同时利用其原生压缩特性缩减向量存储。
- 交付责任
- Cohere 提供 Model Vault 托管基础设施及 Cohere Embed 嵌入模型,支持离线批量嵌入摄取与在线语义搜索。
- 披露结果
- 在线场景下 Cohere Embed 达到 90.7% top-10 召回率和 77 毫秒中位检索延迟;离线负载下 Model Vault 带来约 2.7 倍的单位成本吞吐量提升,且自动扩缩容应对峰值更快速;在无检索退化的情况下将向量存储空间缩减至原来的 1/4。
AI agent retrieval: How Ada scales with Cohere
针对对延迟高度敏感的工作负载,检索面临严苛的延迟要求,多租户服务难以充分满足该需求。
- 流程与架构
- Ada 将 Cohere Embed 接入其既有 AWS 架构中,采用专用计算与独立部署模式运行嵌入模型,与现有的智能体基础设施保持兼容。
- 交付责任
- Cohere 提供实操基准测试和实验以协助确定合适配置,作为检索伙伴支持 Ada 在 AWS 环境(如 SageMaker 或 Vault)中的部署与运行。
- 披露结果
- Ada 在保留既有智能体模型和基础设施的前提下优化了检索能力,在延迟敏感型工作负载中获得了部署灵活性、性能和运维便利,并建立了可持续演进的检索架构。
How CoreWeave used Cohere North to transform its customer support in 90 days
面对业务需求快速增长,CoreWeave希望精简支持系统以减少第三方工具并提升自动化水平;其客户包含顶尖AI实验室与跨国企业,停机成本极其高昂,要求必须快速将客户对接到最合适的工程师手中。
- 流程与架构
- 将Cohere North直接嵌入到其基于Slack的工作流中,实现自动化分诊与上下文收集。
- 披露结果
- 在90天内完成客户支持体系转型,提升了路由分发准确率,缩短了问题解决时间,保持了强劲的客户满意度,使支持人员和工程师能提供更快、更高质量的服务,并为进一步落地Agentic AI铺平了道路。
业务动态
与加拿大和英国政府合作推广公共部门AI应用
Cohere与加拿大及英国政府达成合作,扩大人工智能在公共部门的应用。
收购Ottogrid
Cohere收购了位于温哥华的平台Ottogrid,该平台开发用于自动化特定市场研究的企业工具。
签署加拿大自愿AI行为准则
Cohere签署了加拿大针对人工智能的自愿行为准则,以促进先进生成式AI系统的负责任开发和管理。
签署白宫AI风险应对自愿承诺
Cohere成为签署白宫关于AI风险测试、报告和研究措施自愿承诺的15家科技公司之一。
英伟达投资生成式AI初创公司Cohere
Nvidia向生成式人工智能初创公司Cohere进行投资
成立非营利研究实验室Cohere Labs
Cohere成立了Cohere Labs(此前称为Cohere For AI),作为一个非营利性研究实验室和社区,致力于贡献开源的基础机器学习研究。
Google Cloud与自然语言处理初创公司Cohere就TPU建立多年期合作
Google Cloud与Cohere达成围绕TPU的多年合作协议
Google Cloud合作支持基础设施与部署
Google Cloud宣布将利用其基础设施支持Cohere的平台,其TPU将被Cohere用于产品的开发与部署。
Cohere完成4000万美元A轮融资,推进自然语言处理普及与安全
多伦多自然语言处理初创公司Cohere获得4000万美元A轮融资,旨在让自然语言处理对各企业更加安全和普及
Cohere to acquire AISLE to advance cyber-resilient sovereign AI
Cohere宣布将收购AISLE以推进具备网络弹性的主权AI。
资料来源
公司自述、文档记载与研究归纳分别标注;采集不等于独立核验。
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n 2025, they expanded to Montreal, Canada, [ 23 ] Paris, [ 24 ] and Seoul. [ 25 ] [ 26 ] In May 2025, Cohere acquired Ottogrid, a Vancouver-based platform that develops enterprise tools for automating certain kinds of market research. [ 27 ] In June 2025, it was announced that Cohere had partnered with the governments of Canada and the United Kingdom to expand the use of AI in the public sector. [
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ith no measurable retrieval degradation. Ada , the trusted leader in agentic customer experience (ACX), helps other businesses — from airlines to payments to retail — autonomously resolve support customer service inquiries. Behind these actions are AI agents that each customer configures with its own knowledge, brand voice, and processes, running on Ada's Reasoning Engine. For instance, the type o
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een clear benefits from running its embedding models on dedicated deployments rather than multi-tenant services, particularly for latency-sensitive workloads. Says Melidis: “Dedicated compute for embedding models was new for us. This change showed how much a dedicated deployment matters for retrieval when latency is of utmost concern.” Today, Ada can use its existing AWS environment for deployment
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for the development and deployment of their products. [ 14 ] [ 15 ] In June 2022, Cohere launched Cohere Labs (previously called Cohere For AI), a nonprofit research lab and community to contributing open-source, fundamental machine learning research. It was led by Sara Hooker , a former research scientist at Google Brain [ 16 ] until her departure in September 2025. Cohere Labs is now led by Marz
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nership rooted in customer success, now and for the future Through the process, Cohere provided hands-on benchmarking and experiments to find the right configuration, helping solidify Cohere as a trusted retrieval partner for Ada. Says Melidis, “Whether we were using SageMaker or Vault, we felt like there wasn't a strong pressure. The teams just wanted us to be successful.” The Ada team has also s
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f answer a financial services company gives a banking customer will be different than the one an airline gives a traveler whose flight was just cancelled. But before AI agents can generate the right answers, they must find the right information. That’s where retrieval comes in. Every customer interaction begins with retrieval, giving AI agents the information they need to resolve conversations. “I
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026 4 minute read Ada finds the right ingredients for faster, more efficient AI agents Key takeaways Accelerate AI agent retrieval: Achieved 77 ms median latency and 90.7% top-10 recall with Cohere Embed on Amazon SageMaker AI. Improve cost efficiency: Delivered 2.7x greater throughput-per-dollar for offline embedding with Cohere Model Vault. Reduce storage by 4x: Cut vector storage requirements w
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VPCs Security Protect your data at every stage See deployment options By Industry Financial Services Public Sector Technology Telecommunications Energy and Utilities Healthcare Life Sciences Manufacturing Featured Model Vault provides fully-isolated, performant inference with Saas simplicity Insights Customer Stories For Developers Developers Models Overview Docs Discord LLM University Connect Par
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red CoreWeave’s support staff and engineers to deliver faster, higher-quality support, paving the way for further agentic AI adoption. The promise of AI agents to help companies improve their customer service is clear. So far, though, only a few organizations have turned that vision into reality. CoreWeave , a global AI cloud leader based in the US, is acutely aware that solving customers’ problem
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Ada's scale — thousands of customer knowledge bases, some containing tens of thousands of articles — results quickly compounded. The team reduced its vector storage footprint by 4x with no measurable retrieval degradation. "It was literally a free win,” says Melidis. Better retrieval gave Ada's agents better information to work with, supporting its north star metric: successful resolution. A part
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alified to solve their issues. It has a simple motto: Customer first, always . “Every interaction has to protect their time and keep their systems running” John Mancuso, VP of Customer Experience, CoreWeave The initial challenge Facing rapid growth in demand, CoreWeave wanted to streamline its support system by reducing the number of third-party tools, increasing automation, and reducing the amoun
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latency budget that left little room for retrieval Scale: Perform across regions at multi-tenant scale A structured approach to find a solution Ada conducted a structured evaluation to find a solution for both offline and online use cases. "We started in a very structured way—a four-way bakeoff,” explains Melidis. The bakeoff, a systematic, time-bound testing period, vetted each approach against b
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ndustries Why leading teams trust Cohere technology Ada finds the right ingredients for faster, more efficient AI agents Read more technology How CoreWeave used Cohere North to transform its customer support in 90 days Read more technology Integrating Cohere into Draftwise boosted the quality of search results by 30% Read more The team at Cohere has made foundational contributions to generative AI
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Tube CFO Martin Kon as president" . The Globe and Mail . Retrieved October 3, 2023 . 1 2 "Google Cloud teams up with NLP startup Cohere on multiyear partnership around TPUs" . TechCrunch . November 17, 2021 . Retrieved December 31, 2021 . 1 2 Cohere (September 7, 2021). "Cohere Raises $40 Million in Series A Financing to Make Natural Language Processing Safe and Accessible to Any Business" . Globe
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Small Translate Machine translation model Parse New Document parsing model Embed New Semantic representation model Rerank New Retrieval optimization model Models Overview Product Products Overview Total Cost of AI Ownership Pricing Featured North 2: Cohere's latest platform update — with 15+ new features Deploy Model Vault Dedicated model inference platform Private Deployments On-prem or isolated
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flexibility, performance, and operational ease. Cohere Embed could fit into its existing architecture, allowing the team to optimize retrieval while preserving the models and infrastructure already supporting its agents. The project gave Ada more than a point solution. It established a retrieval architecture that the team can continue to evolve as its AI stack changes. With Cohere already prepari
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f retrieval is slow, our agent is slow and everything that stems from it... and if retrieval is wrong, then the agent is wrong as well,” explains Christos Melidis, PhD, Staff Machine Learning Scientist at Ada. The initial challenge Ada’s online use case: every millisecond counts Now imagine you are calling in, asking an AI agent a question and hearing an unnatural pause before every answer. A few
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as geographically closer to Ada’s services, it was the sensible choice for the latency-sensitive live conversations. With Cohere Embed on SageMaker AI, Ada achieved median retrieval latency of 77 milliseconds (ms) — only 0.077 seconds for that step in the response process. For a caller, shaving time from retrieval helps reduce the silence between asking a question and hearing the agent respond. Fo
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etter it is.” In other words, when voice enters the chat (literally), the stakes are higher. Three requirements Within the online use case, Ada set a tighter latency budget for voice than its previous retrieval setup could deliver consistently. The solution had to meet three requirements: Quality: Find the right information in each customer's knowledge base Latency: Fit within an end-to-end voice
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cal representations that make it possible to search for semantically similar information. “We saw better performance, better quality in the answers, and a better experience for the clients.” Christos Melidis, PhD, Staff Machine Learning Scientist, Ada The recipe for success emerges In the online use case, Cohere Embed quickly emerged as a star, achieving 90.7% top-10 recall. Because SageMaker AI w
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mocratize natural-language AI" . Fast Company . Archived from the original on December 22, 2021 . Retrieved December 31, 2021 . 1 2 3 4 Goldberg, Natalie (June 8, 2023). "Nvidia invests in Google-linked generative A.I. startup Cohere" . CNBC . Archived from the original on October 6, 2023 . Retrieved October 6, 2023 . 1 2 Silcoff, Sean (September 7, 2021). "Toronto AI startup Cohere raises US$40-m
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th whom Gomez had done research at FOR.ai. [ 10 ] [ 11 ] All of the co-founders attended the University of Toronto . [ 12 ] Gomez is the company's CEO. [ 11 ] In December 2022, Martin Kon, the former CFO of YouTube , became president and COO. [ 13 ] In November 2021, Google Cloud announced they would help power Cohere's platform using their infrastructure, and Cloud's TPUs would be used by Cohere
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e(s) of Work How will AI change the way we work? Aya Models Multilingual AI at scale All Papers Initiatives Research Scholars Finding the new generation of ML talent Open Science Community Championing global, open science Catalyst Grants Supporting impactful ML endeavors Resources Blog Hugging Face Events Featured The future of work debate has an evidence problem About Careers Newsroom Customer st
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gn on to a voluntary White House commitment on measures for testing, reporting, and research on the risks of AI. [ 18 ] On September 27, 2023, it was announced that Cohere had also signed Canada's voluntary code of conduct for AI, to promote the responsible development and management of advanced generative AI systems. [ 19 ] In 2024, Cohere opened an office in New York City. [ 20 ] [ 21 ] [ 22 ] I
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s fast is fundamental to success. The pioneers who rely on CoreWeave’s infrastructure and support include the world’s top AI labs and global enterprises. Their time is highly valuable; just an hour of downtime can be extremely expensive. That’s why CoreWeave has built its support culture on the principle of "Direct to Expert," a commitment to connecting customers quickly with the engineers most qu
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Enterprise AI: Private, Secure, Customizable | Cohere Skip to content Rerank 5 is here: sharper search, fewer tokens. Now with Context Focus. Learn more Products Solutions Resources Blog Research Company Sign in Request a demo Platform North Enterprise-ready AI for business Compass Intelligent search and discovery Models Command Generative language models Transcribe Speech recognition model North
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r offline workloads, Model Vault delivered approximately 2.7x greater throughput-per-dollar than Ada's self-hosted setup. Its managed autoscaler handled republishing spikes faster than Ada's self-managed scaling. Across the retrieval system, Embed enables compression without performance impact. Because Embed supports compression natively, Ada did not need to build its own quantization pipeline. At
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025 . ↑ Satariano, Adan (April 24, 2026). "A.I. Start-Ups From Canada and Germany Merge to Take On Silicon Valley" . The New York Times . Retrieved April 24, 2026 . ↑ Scott, Josh (September 8, 2021). "Cohere raises $40 million USD to make natural language processing more accessible" . BetaKit . Retrieved December 31, 2021 . ↑ Sullivan, Mark (September 7, 2021). "Ex-Googlers raise $40 million to de
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ieh Fadaee. [ 17 ] In December 2022, Cohere released a multilingual model for understanding text that would work with over 100 languages, to help users search for documents by meaning instead of keywords. This type of process was not previously widely available in languages other than English. [ 13 ] On September 12, 2023, it was announced that Cohere had become one of fifteen tech companies to si
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ur rules. North by Cohere is a complete agentic enterprise AI platform that you control and deploy on your terms. Trusted by industry leaders and developers worldwide AI for Empowerment Your freedom. Your focus. Cohere keeps it that way. Learn how AI helps you reclaim time for what truly moves you. Explore now Purpose-built AI solutions north platform North: Enterprise AI Without Compromises A ful
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re AI has flown under the radar. That may be about to change" . Venture Beat . Archived from the original on October 6, 2023 . Retrieved October 3, 2023 . ↑ "AI startup Cohere raises US$40-million for natural language software: Globe and Mail" . University of Toronto News . September 8, 2021 . Retrieved December 31, 2021 . 1 2 3 O'Kane, Josh (December 14, 2022). "Rising AI startup Cohere hires You
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ting reveals a key insight: two use cases, two solutions For offline knowledge-base indexing, Ada uses Cohere Model Vault . Dedicated, Cohere-managed infrastructure runs models privately and at scale, and supports bulk embedding and ingestion. For its online retrieval path, Ada self-hosts Cohere Embed on dedicated Amazon SageMaker AI instances. Cohere Embed converts content and queries into numeri
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milliseconds might sound insignificant on paper, but inside a conversation, you feel it. A fast retrieval model gives customers more confidence that their questions will be answered in a timely manner instead of wondering whether the call dropped. “If you're on the phone, you don't have a visual. You don't see an indicator blinking. You're hearing silence,” explains “The smaller the silence, the b
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AI agent retrieval: How Ada scales with Cohere | Cohere Skip to content Rerank 5 is here: sharper search, fewer tokens. Now with Context Focus. Learn more Products Solutions Resources Blog Research Company Sign in Request a demo Platform North Enterprise-ready AI for business Compass Intelligent search and discovery Models Command Generative language models Transcribe Speech recognition model Nort
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oth of Ada's workloads. The bakeoff’s ingredients: 15,000 evaluation queries Online and offline workloads Four embedding approaches Three requirements: quality, latency, and scale One north star: successful resolution From the start, the testing challenged one of Ada’s assumptions: that a single deployment could efficiently serve both workloads. Two use cases demanded two technology solutions. Tes
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5 minute read How CoreWeave used Cohere North to transform its customer support in 90 days Key takeaways CoreWeave transformed its customer support within 90 days by embedding Cohere’s North directly into its Slack-based workflows . North’s automated triage and context-gathering improved routing accuracy, accelerated resolution times, and supported strong customer satisfaction scores. North empowe
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tners Events Webinars Merch Store Featured Ada finds the right ingredients for faster, more efficient AI agents Blog The latest news, launches, and insights Read more Cohere to acquire AISLE to advance cyber-resilient sovereign AI North 2: Enterprise AI without compromises Introducing Embed 5—A new family of frontier embedding models Research Cohere Labs Cohere’s ML research lab Explorations Futur
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ly ownable agentic platform built to bring peak security, intelligence, cost efficiency, and control together. Explore North cohere models Our models. Your business. Tools for generative AI, advanced search, and multilingual capabilities—built to keep your enterprise in full control. Explore models model vault Scalable, secure AI deployment Model Vault provides fully-isolated performance inference
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ories Enterprise AI case studies and success stories See how our customers and partners streamline operations, deliver intelligent user experiences, and transform business outcomes with enterprise-ready AI. Request a demo Ada finds the right ingredients for faster, more efficient AI agents How CoreWeave used Cohere North to transform its customer support in 90 days Fujitsu launches Takane AI model
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in partnership with Cohere Draftwise boosts legal productivity with Cohere's AI models BambooHR optimizes AI search and retrieval Oracle launches over 100 generative AI use cases with Cohere Atomicwork builds Atom AI with Cohere
