Cohere
工具信息
评价
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嵌入
替代品
Cohere 工具信息
什么是Cohere？
Cohere是一个为客户支持而设计的对话式AI平台。它帮助客户支持团队更快解决问题并降低成本。通过利用AI技术，Cohere从之前的工单中找到答案，并为客户的问题提供即时解决方案。
如何使用 Cohere？
要开始使用Cohere，只需通过网站预订演示。在演示过程中，您可以通过共享您的帮助中心链接来了解如何训练机器人。这个AI技术的机器人可以像真的客户一样理解并回答客户问题。此外，您还可以使用Cohere将支持文章和以往的对话即时转换为个性化答案。您还可以使用Cohere的先进分析功能Cardina来识别客户趋势并快速解决问题。
Cohere 的核心功能
面向快速增长的客户服务团队的自动化
自动解决多达60%的工单
通过任何渠道向客户提供即时个性化答案
逐步引导用户解决问题
代表客户执行操作
将支持文章和以往对话转换为个性化答案
使用先进的分析功能识别并预测客户趋势
通过语言理解提供准确答案的AI
生成式AI从客服回答中提取答案
自动回答重复问题
Cohere 的使用案例
#1
扩大客户支持而无需增加人员
#2
更快解决工单并降低成本
#3
提高客服人员满意度和客户体验
#4
增加自助解决方案
#5
增强客户忠诚度和保留率
#6
在Web和移动平台上提供个性化支持
#7
提高客户体验效率并加快服务速度
Cohere 支持邮箱 & 客户服务联系 & 退款联系等
以下是 Cohere 支持邮箱含客户服务: sales@cohere.io .
Cohere 公司信息
Cohere 公司名字: Caldera Labs Inc. .
Cohere 公司地理位置: 298 5th Avenue, 7th Floor New York, NY 10001. USA.
更多关于Cohere, 请访问 the about us page(https://cohere.io/company).
Cohere Twitter
Cohere Twitter链接: https://twitter.com/coherehq
Cohere 评价 (0)
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Cohere数据分析
Cohere 网站流量分析
地理位置
Top 5 国家/地区
51.36%
11.66%
10.69%
10.44%
7.83%
Dec 2022 - Mar 2025 仅桌面设备
Cohere 启动嵌入功能
使用网站徽章推动社区对 Toolify 启动的支持。它们很容易嵌入到您的主页或页脚。
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社交媒体聆听
AI M&A: Billion Dollar Acquisitions Reshape AI Landscape
Today on The AI Breakdown Brief: - Databricks acquires Mosaic for $1.3B https://venturebeat.com/data-infrastructure/databricks-is-acquiring-mosaicml-for-a-jaw-dropping-1-3-billion/ - Ramp acquires Cohere.io https://techcrunch.com/2023/06/26/as-the-generative-ai-craze-rages-on-fintech-ramp-acquires-ai-powered-customer-support-startup-cohere-io/ - Thompson Reuters acquires legal AI firm CaseText for $650M https://www.reuters.com/markets/deals/thomson-reuters-acquire-legal-tech-provider-casetext-650-mln-2023-06-27/ - Verge surveys 2000 people on AI https://www.theverge.com/c/23753704/ai-chatgpt-data-survey-research - MerlynMind releases education focused large language models https://twitter.com/MerlynMind/status/1673392877899255808 - Waldo 2.0 is drone object identification https://twitter.com/StephanSturges/status/1646568636532903943 - Whale song AI https://twitter.com/TerraMaterFS/status/1563126936607817731 The AI Breakdown helps you understand the most important news and discussions in AI. Subscribe to the podcast version of The AI Breakdown wherever you listen: https://pod.link/1680633614 Learn more: https://breakdown.network/ 0:00 Databricks acquires Mosaic for $1.3B 2:26 Ramp acquires Cohere.io 2:55 Thompson Reuters acquires legal AI firm CaseText 3:33 Verge surveys 2000 people on AI 6:25 MerlynMind releases education focused large language models 7:16 Waldo 2.0 is drone object identification 8:13 Whale song AI
Rethinking how we Scaffold AI Agents - Rahul Sengottuvelu, Ramp
Diagrams, algorithms, and handcrafted heuristics have long played a role in constructing AI agents, but are these traditional scaffolding techniques holding us back? Many current approaches lean too heavily on manual design, neglecting the “bitter lesson” that history has taught us: leveraging massive computation and generic methods often trumps tailored engineering. What if we could rethink our scaffolding strategies for AI agents—aligning them with decades of insight from the broader AI research community? In this talk, Rahul Sengottuvelu, Head of Applied AI at Ramp and co-founder of Cohere.io, will explore how embracing the bitter lesson can transform our approach to building AI agents. Attendees will gain actionable strategies to design more robust, scalable systems that minimize over-engineering while maximizing the power of general-purpose learning. Recorded live at the Agent Engineering Session Day from the AI Engineer Summit 2025 in New York. Learn more at https://ai.engineer and purchase tickets to our next event, the AI Engineer World's Fair, in SF June 3 - 5 here: https://ti.to/software-3/ai-engineer-worlds-fair-2025 About Rahul Rahul Sengottuvelu is the Head of Applied AI at Ramp. Before that, he co-founded Cohere.io, a customer support automation platform that used advanced AI to resolve support tickets more accurately. Cohere.io was acquired by Ramp in May 2023. He is also the author of Jsonformer, a constrained decoding library for LLMs.