Synthetic document data, OCR training, Document AI, and privacy-safe ML workflows.
Your model hits 94% character accuracy on printed text and 61% on handwritten fields. This isn't a model architecture problem. It's a training data distribution problem — and once you see it clearly, the fix is straightforward.
A practical guide to how synthetic document data works, what makes it structurally different from anonymized or augmented real data, and when your ML pipeline actually needs it.
Random data generators like Faker produce independent field values with no structural coherence. Here's why that matters for document extraction models, and what to use instead.
