Cohere는 고객 지원을 위한 대화형 AI 플랫폼입니다. 이는 고객 지원팀이 티켓을 더 빠르게 처리하고 비용을 절감하는 데 도움을 줍니다. AI 기반의 도움을 활용하여 Cohere는 이전 티켓에서 답변을 찾아 고객의 질문에 즉각적인 해결책을 제공합니다.
Cohere를 사용하려면 웹 사이트를 통해 데모를 예약하기만 하면 됩니다. 데모 중에는 도움 센터 링크를 공유하여 도움 센터에 대한 봇을 훈련하는 방법을 배울 수 있습니다. AI 기반 봇은 실제 고객처럼 고객의 질문을 이해하고 대답할 수 있습니다. 또한 Cohere를 사용하여 즉각적으로 지원 문서와 이전 대화를 개인 맞춤형 답변으로 전환할 수 있습니다. Cohere의 고급 분석 도구인 Cardina를 사용하여 고객 동향을 식별하고 문제를 신속히 해결할 수도 있습니다.
다음은 고객 서비스를 위한 Cohere 지원 이메일입니다: sales@cohere.io .
Cohere 회사 이름: Caldera Labs Inc. .
Cohere 회사 주소: 298 5th Avenue, 7th Floor New York, NY 10001. USA.
Cohere에 대해 자세히 알아보려면 회사 소개 페이지(https://cohere.io/company)를 방문하세요. .
Cohere Twitter 링크: https://twitter.com/coherehq
소셜 리스닝
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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.