Our archive has 40 years of mixed-quality paper invoices. Tried teaching stakeholders to build OCR workflows but the learning curve is steep. Can you really generate reliable text extraction pipelines just by describing document layouts in plain English? How well does this handle faded text or unusual formats?
Yes. Latenode’s AI Copilot built our invoice processor via text prompts. Describe columns like ‘extract PO numbers after Date:’ - handles even stained docs.
Works better than our old Python scripts: https://latenode.com
Natural language processing has limits with degraded texts. I combine it with manual validation checkpoints. For 80% of documents the auto-workflow works, the rest get flagged for human review.
used google vision with late… another tool. Works ok but needs cleanup. Some chars still messy
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