PDF OCR Tool
Extract searchable text layers from scanned PDF pages and digital images with browser-native neural-engine precision.
Drop your scanned PDF or Image here
Supports PDF, JPG, PNG, WebP · Max 50MB
How It Works
Upload Scans
Drag and drop scanned PDF pages or document images.
Select Language
Choose from 10+ neural-net supported languages.
Extract & Save
Edit characters in real-time, copy text, or compile searchable PDFs.
Frequently Asked Questions
Is the OCR text extraction secure?
What makes a PDF searchable?
Can it extract multiple languages?
From Picture-of-Text to Actual Text
What OCR can read — and what defeats it
OCR accuracy is decided before the software runs — by the scan itself:
| Source material | Expected accuracy | Notes |
|---|---|---|
| 300 DPI flatbed scan, clean print | Excellent (99%+) | The gold standard |
| Phone photo, good light, flat page | Good | Crop to the page edges first |
| Faded photocopy or carbon copy | Patchy | Boost contrast before OCR if possible |
| Handwriting | Poor to none | OCR engines target printed text |
| Urdu Nastaliq script | Weak | Latin-script engines misread it; expect manual correction |
How a searchable PDF actually works
OCR doesn't replace your scan — it adds an invisible text layer positioned behind the page image. The document looks identical, but now Ctrl+F finds words, text can be selected and copied, and screen readers can speak it. That last part matters for accessibility compliance, and the search part matters the day you need one clause in a 200-page scanned agreement.
OCR's place in the pipeline
OCR comes first, always: run it before converting with PDF to Word (otherwise Word receives a picture), and before extracting tables with PDF to Excel. Compressing is fine afterwards — the PDF compressor preserves the text layer while shrinking the page images that make scanned files huge.