机器学习驱动的票证分类提高了支持效率和贡献者满意度
技术
- 分析与建模 - 机器学习
- 平台即服务 (PaaS) - 应用开发平台
适用行业
- 水泥
- 教育
适用功能
- 采购
- 产品研发
用例
- 时间敏感网络
- 虚拟培训
服务
- 系统集成
- 培训
关于客户
澳鹏是为大规模构建有效人工智能系统的组织提供高质量培训数据的领先提供商。他们于 2020 年 4 月在其解决方案中集成了Figure 8，这是一个由 AI/ML 支持的人机交互数据转换平台。
挑战
澳鹏需要实现其票务系统的自动化，以提高支持效率、缩短票务处理时间并减少贡献者的流失。手动票务会导致分类错误、增加票证处理时间和贡献者流失。
解决方案
Provectus 构建了一个机器学习驱动的解决方案，可以自动对澳鹏贡献者生成的票证进行分类、确定优先级并解决问题。他们建议构建一个基于 ML 的自动票证分类系统，并将其与 ZenDesk 的路由解决方案相结合。 ML 模型是使用 TensorFlow 构建的，可解决标准文本分类问题。
运营影响
数量效益
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