Original Summary

was building an ai invoice parser and spent ages trying to push the accuracy number up. then someone testing it said something that stuck with me, accountants don't want to blindly trust ai on their books, they want to know what to actually check. so instead of only chasing raw accuracy i added a confidence score on every field it pulls out. anything it's not sure about gets flagged before it ever gets exported, instead of quietly hoping nothing slipped through. weirdly it made people trust it more even though the actual accuracy number didn't move. the failure mode went from "wrong answer, nobody notices" to "flagged, 5 second check." anyone else building stuff for finance/legal/medical type use cases run into the same thing, that showing where it's unsure beats chasing a perfect number nobody actually believes anyway   submitted by   /u/Hashtag_Maybe [link]   [comments]

  • 情报分类：商业与市场研究
  • 分类依据：内容涉及商业、投资或市场动态
  • 信息来源：Reddit · SaaS
  • 发布时间：2026/9/28 02:46:33