Built a tax document classifier with Jev.

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Built a tax document classifier with Jev that labels the full corpus at $0.001 per page, 34x cheaper and 6x faster than the prior LLM pipeline.

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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:

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Where this case fits

Filed under agents & workflows, classification & data extraction, finance & trading. In the pattern Jev is built for, the model answers a bounded question per step — and ordinary code acts on the answer, because the answer is already a value rather than a paragraph. Other posts in the same family are on the agents & workflows page.

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Last updated: 2026-09-22 · sources & corrections · every card links to its author's original post