技术
- 分析与建模 - 机器学习
- 网络安全和隐私 - 入侵检测
适用行业
- 建筑物
- 建筑与基础设施
适用功能
- 质量保证
用例
- 假冒产品识别
- 欺诈识别
服务
- 测试与认证
客户
未披露
关于客户
客户是一家主要的欧洲航空公司。它成立于 1928 年,是世界上最古老的运营航空公司之一。客户拥有近 100 架飞机的机队,飞往欧洲、亚洲和北美的 120 多个目的地。
挑战
客户是一家大型航空公司,为数百万乘客提供服务,并与众多商业伙伴合作。他们的地勤办公室每月处理超过 10 000 张发票。发票由近 600 家独立公司和承包商提供。
处理如此大量的不同文档非常耗时,并且需要涉及多个人员和团队。它还延迟了对数据的分析以及因此应采取的任何操作,同时使整个过程容易出错。
客户想探索优化此过程的可能性。
解决方案
他们决定让Objectivity 来寻找一种解决方案,该解决方案可以自动验证文档并更轻松地检测错误。
客观性决定使用 Azure 表单识别器进行文档提取。该团队构建了一个工具,可以对 PDF 文件的结构进行特定的可视化。这是根据发票的实际结构测试表单识别器的结果所必需的。下一步,检查并收集了 200 多张样本发票,作为进一步测试的参考数据集。
然后对该解决方案进行测试和微调,以在发票测试集中实现 95% 以上的数据检测准确率。
运营影响
数量效益
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