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Enhancing Accounts Payable Training Data with Scale Document AI: A Case Study on SAP
技术
- 分析与建模 - 机器学习
- 功能应用 - 企业资源规划系统 (ERP)
适用行业
- 教育
适用功能
- 采购
- 质量保证
用例
- 虚拟培训
- 视觉质量检测
服务
- 测试与认证
- 培训
挑战
SAP 是一家领先的软件公司,在改进其文档处理产品方面面临着挑战,特别是那些处理发票、采购订单和付款建议的产品。该团队拥有大量客户文档,但需要合作伙伴创建一个全面的数据集,以增强其应付账款产品,同时尊重数据所有权、隐私和敏感性。对于高性能模型来说,对高质量数据的需求至关重要。 SAP 需要优质的培训数据来训练模型,以处理和提取英语、德语和西班牙语采购订单和发票中的关键信息。客户数据的可变性(有些客户每周提供数千份文档,而另一些则需要数月时间才能提供相同数量的一小部分),这增加了挑战的复杂性。
关于客户
SAP 是一家领先的软件公司,总部位于德国瓦尔多夫,以开发用于管理业务流程的企业软件和创建促进有效数据处理的解决方案而闻名。 SAP 以其企业资源规划 (ERP) 软件而闻名,旨在帮助各种规模的公司和组织实现业务盈利、持续适应和可持续发展。它们具有广泛的用例,包括文档处理、分析、主数据匹配和流程自动化。在与 Scale 的合作中,他们专注于改进文档处理方面的产品,特别是那些处理发票、采购订单和付款建议的产品。
解决方案
Scale 凭借其在各种用例中标记数据方面的深厚专业知识,提供了解决方案。该团队提供了跨三种语言、多种文档类型和 200 多个独特字段的高质量标记数据。他们还必须处理包含个人身份信息 (PII)(例如姓名、电话号码和电子邮件)的文档中字段的复杂性。这些需要用语义相似但不同的示例替换,以保护数据隐私。尽管面临这些挑战,Scale 仍以近乎完美的精度交付了标记数据,并快速实现了大批量生产。他们与 SAP 密切合作,了解 SAP 业务文档处理 (BDP) 模型的技术和业务要求,利用机器学习驱动的预标签和 Scale 的全球标签操作相结合来提供高质量的数据。
运营影响
数量效益
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