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CASE FILE / Documents & OCR
Built a tax document classifier with Jev
Built a tax document classifier with Jev. We ingest thousands of tax documents using an LLM pipeline I built last tax season. I read multiple articles as late as April this year claiming AI fails at tax document classification. Wasn't the case back then, and it's proved wrong again now. Jev classifies 100% of our tax document corpus at $0.001 per page. 34x cheaper and 6x faster than the LLM setup. Open sourcing it: https://t.co/gInVHudFRn
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Nakshatra Saxena · @nedwize
Original post
Built a tax document classifier with Jev. We ingest thousands of tax documents using an LLM pipeline I built last tax season. I read multiple articles as late as April this year claiming AI fails at tax document classification. Wasn't the case back then, and it's proved wrong again now. Jev classifies 100% of our tax document corpus at $0.001 per page. 34x cheaper and 6x faster than the LLM setup. Open sourcing it: https://t.co/gInVHudFRn
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Chinese translation
与Jev一起构建税务文件分类器。 我们使用我上个纳税季节建立的LLM管道获取了数千份税务文件。 直到今年四月，我还阅读了多篇文章，声称人工智能在税务文件分类方面失败。当时不是这样，现在又被证明是错误的。 Jev将我们100%的税务文件库归类为每页0.001美元。 比LLM设置便宜34倍，速度快6倍。 开源：https://t.co/gInVHudFRn
What this case shows
- Document pipelines need routing, not essays
- Use choice/score to send a file downstream
- Fall back to a heavier model when unsure