What should I use for OCR on scanned forms with handwritten notes?

For scanned forms with handwritten notes, the best OCR choice depends on how much handwriting accuracy you need:

Good options

• Google Cloud Vision / Document AI
  Strong general OCR, decent on handwriting, good for forms and structured documents.
• Microsoft Azure AI Document Intelligence
  Very good for form extraction and structured data; handwriting support is solid.
• AWS Textract
  Excellent for printed forms and tables; handwriting support exists but is usually less strong than Google/Azure for freeform notes.

If handwriting is messy or important

• Consider specialized handwriting OCR or a human-in-the-loop workflow.
  No OCR system is perfect on cursive, faint, or messy handwritten notes.

Open-source / local options

• Tesseract
  Good for printed text, but generally weaker for handwriting.
• PaddleOCR
  Better than Tesseract in many cases, but handwriting performance still varies.
• docTR
  Worth testing, especially for document layouts, though handwriting results depend on the scan.

My practical recommendation

• If you want the best all-around cloud solution: Google Document AI or Azure Document Intelligence
• If the forms are mostly printed fields with a few handwritten annotations: AWS Textract or Azure
• If you need on-prem / offline: test PaddleOCR and Tesseract, but expect lower handwriting accuracy

Tip

For scanned forms, the biggest improvements often come from:

• de-skewing and denoising scans
• high-resolution input
• detecting form structure separately from OCR
• using field-specific validation after OCR

If you want, I can recommend a specific OCR stack based on:

1. volume,
2. handwriting quality,
3. whether you need cloud or local, and
4. whether the forms are fixed-layout.