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boost.ai
概述
公司介绍
Boost.ai 站在企业级对话式人工智能的前沿。Boost.ai 致力于实现人与组织之间无与伦比的互动,利用尖端技术负责任地突破人工智能的界限。其专有的自学习人工智能平台使企业能够大规模自动化互动,提高效率并推动积极成果。
物联网应用简介
boost.ai 是基础设施即服务 (iaas), 可穿戴设备, 和 平台即服务 (paas)等工业物联网科技方面的供应商。同时致力于航天, 汽车, 建筑物, 水泥, 城市与自治市, 电子商务, 教育, 金融与保险, 零售, 和 电信等行业。
技术栈
boost.ai的技术栈描绘了boost.ai在基础设施即服务 (iaas), 可穿戴设备, 和 平台即服务 (paas)等物联网技术方面的实践。
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设备层
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边缘层
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云层
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应用层
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配套技术
技术能力:
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弱
中等
强
实例探究.
Case Study
Conversational AI Enhances Internal Support and Efficiency at Aker BP
Aker BP, one of Norway’s largest oil exploration and development companies, faced a significant challenge in providing efficient internal support to its approximately 2,000 employees across five offices and various offshore sites. Initially, the company relied on administrative assistants to handle queries related to IT, HR, training, supply chain management, and more. However, as the company grew, this approach became less efficient, with support staff becoming overwhelmed with repetitive tasks and queries. These tasks, while important, consumed significant amounts of time, diverting them from key tasks such as recruitment, training, and organizational development. Aker BP sought to move away from a reliance on human support and aimed to achieve administrative self-service by increasing employee efficiency while maintaining the high level of service they were accustomed to. The company aimed to create a central hub of knowledge that employees could easily access for answers, while still having support staff available for more complex requests.
Case Study
Enhancing Customer Experience in Insurance with Conversational AI
Aspire General Insurance Services, a California-based private passenger auto liability and physical damage carrier, was facing challenges in managing customer service efficiently. The company, which handles all aspects of the insurance process, was relying heavily on human agents for customer interaction and professional conversations across the insurance cycle. This reliance was making optimal customer service cumbersome and time-consuming. The customer service team, including chat services, was supported exclusively by human agents, which limited the resolution time for customer chats and led to elevated wait times for simple customer inquiries. Depending on various factors like staff turnover and external pressures, customers sometimes had to wait for as long as half an hour to be served.
Case Study
Íslandsbanki's AI-Powered Virtual Agent Automates 50% of Chat Traffic in Six Months
Íslandsbanki, one of the three major banks in Iceland, was facing a challenge in managing its customer service. The bank was trying to make the banking experience more digital and less branch-heavy, while simultaneously improving its infrastructure. They identified a growing desire amongst their customer base to interact via online channels. However, during incidents where the bank’s app or website login experienced downtime, calls to the contact center would skyrocket, potentially leaving customers hanging after phone lines closed for the day. The bank did not have a 24/7 call service, and they needed to control what was happening in the call center. They realized that a chatbot could be a viable alternative channel to manage the increasing demand for online chat as opposed to phone calls.