Enhancing customer experience is essential for business success, particularly as service demands grow in scale and complexity. Generative artificial intelligence and Large Language Models (LLMs) have empowered intelligent interaction systems to deliver efficient, personalized, and 24/7 support. In practice, intelligent interaction systems encounter several challenges: (1) Constructing high-quality data for cold-start training is difficult, hindering self-evolution and raising labor costs. (2) Multi-turn dialogue performance remains suboptimal due to inadequate intent understanding, rule compliance, and solution extraction. (3) Frequent evolution of business rules affects system operability and transferability, constraining low-cost expansion and adaptability. (4) Reliance on a single LLM is insufficient in complex scenarios, where the absence of multi-agent frameworks and effective collaboration undermines process completeness and service quality. (5) The open-domain nature of multi-turn dialogues, lacking unified golden answers, hampers quantitative evaluation and continuous optimization. To address these challenges, we introduce WOWService, an intelligent interaction system tailored for industrial applications. With the integration of LLMs and multi-agent architectures, WOWService enables autonomous task management and collaborative problem-solving. Specifically, WOWService focuses on core modules including data construction, general capability enhancement, business scenario adaptation, multi-agent coordination, and automated evaluation. Currently, WOWService is deployed on the Meituan App, achieving significant gains in key metrics, e.g., User Satisfaction Metric 1 (USM 1) -27.53% and User Satisfaction Metric 2 (USM 2) +25.51%, demonstrating its effectiveness in capturing user needs and advancing personalized service.

翻译：提升客户体验对商业成功至关重要，尤其在服务需求规模和复杂性不断增长的背景下。生成式人工智能与大语言模型（LLMs）赋能智能交互系统，使其能够提供高效、个性化且全天候的支持。实践中，智能交互系统面临若干挑战：（1）冷启动训练所需高质量数据构建困难，阻碍系统自我进化并推高人力成本。（2）由于意图理解、规则遵从与解决方案提取能力不足，多轮对话性能仍不理想。（3）业务规则频繁演进影响系统可操作性与可迁移性，制约低成本扩展与适应性。（4）复杂场景中依赖单一LLM能力不足，缺乏多智能体框架与有效协作会损害流程完整性与服务质量。（5）多轮对话的开放域特性及统一标准答案的缺失，阻碍了定量评估与持续优化。为应对这些挑战，我们提出了WOWService，一个为工业应用定制的智能交互系统。通过集成LLMs与多智能体架构，WOWService实现了自主任务管理与协同问题解决。具体而言，WOWService聚焦于数据构建、通用能力增强、业务场景适配、多智能体协调与自动化评估等核心模块。目前，WOWService已部署于美团App，在关键指标上取得显著提升，例如用户满意度指标1（USM 1）降低27.53%，用户满意度指标2（USM 2）提升25.51%，证明了其在捕捉用户需求与推进个性化服务方面的有效性。