📄 中文摘要
Clarus Care作为一家医疗保健联络中心解决方案提供商，与AWS生成式AI创新中心（GenAIIC）团队合作，开发了一款由生成式AI驱动的联络中心原型。该原型旨在通过自动化语音机器人和聊天界面实现会话式交互和多意图解析。解决方案的核心在于整合了Amazon Bedrock，利用其强大的基础模型能力来处理复杂的自然语言理解和生成任务。系统能够识别用户提出的多个意图，并同时进行处理，显著提升了用户体验和问题解决效率。为支持业务增长，该架构设计了可扩展的服务模型，确保在高并发请求下也能保持稳定性能。
📄 English Summary
How Clarus Care uses Amazon Bedrock to deliver conversational contact center interactions
Clarus Care, a prominent healthcare contact center solutions provider, collaborated with the AWS Generative AI Innovation Center (GenAIIC) team to engineer a pioneering generative AI-powered contact center prototype. This innovative solution is meticulously designed to facilitate highly conversational interactions and achieve multi-intent resolution through the seamless integration of an automated voicebot and a sophisticated chat interface. At its core, the prototype leverages Amazon Bedrock, harnessing its robust foundation models to process intricate natural language understanding and generation tasks. The system excels at simultaneously identifying and addressing multiple user intents, thereby significantly enhancing user experience and streamlining problem resolution. To accommodate future expansion and fluctuating demand, the architecture incorporates a scalable service model, ensuring consistent performance even during peak loads. Recognizing the critical nature of healthcare communications, the solution is equipped with integrated human transfer capabilities. Users can initiate a transfer to a human agent upon request, or the system can automatically trigger a transfer in urgent or complex scenarios, guaranteeing accurate information dissemination and appropriate handling of high-stakes issues. Furthermore, the prototype integrates a comprehensive analytics pipeline. This pipeline systematically collects and analyzes user interaction data, voicebot performance metrics, and human transfer patterns. These invaluable insights empower Clarus Care to continuously iterate and refine its AI models, optimize interaction flows, and ultimately elevate the overall operational efficiency and customer satisfaction of its contact center.