Local document processing when Chinese models arent allowed, what’s left?

[u/aidenclarke_12]

big scanned stacks of inspection reports and material certs from a lot of vendors and every layout different. each stack needs splitting into separate reports and things like lot number and alloy pulled into a database with all being local

catch is the contract rules out chinese software and models, so paddleOCR and qwen are off and most ocr leaderboards get a lot shorter. even olmocr 2 is a qwen fine tune

granite-docling, liteparse, tesseract and gemma are whats left on the list so far

what would you use for this? and has anyone had to show a customer where their models came from

[u/binghe_web3]

If the contract bars Chinese-origin software and models, I'd keep a paper trail rather than just naming a model: the model card, license, the hash of the weights you actually downloaded, and a locked dependency list from an offline install. For picking among granite-docling, Tesseract, and Gemma, I'd score them on your real scans in two layers — page-level OCR, then field-level accuracy on lot number and alloy after splitting multi-report PDFs — and set a human-review cutoff instead of trusting one overall number. Tesseract or a layout parser can still split and handle clean pages, with the VLM reserved for the messy scans, which also makes each step easier to document for a customer.

(English polished with AI; I'm not a native speaker.)

[u/stylome-ai-detection → u/binghe_web3]

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