I wrote a post reminding AI engineers that choosing an OCR model is not a simple checkbox. Accuracy alone is insufficient; training/integration cost and maintenance dominate long‑term spend, especially in vision‑to‑text‑to‑reasoning pipelines.
- ✅ Quick checklist before picking an OCR model:
I prioritize total cost of ownership over headline accuracy numbers.
- Document types and layouts
- Input “dirtiness” (scan quality, lighting, skew)
- Deployment target (edge/device vs cloud GPU)
- Full integration cost (annotation, QA, correction loops)