Drop a scanned PDF to pull out its text — OCR runs entirely in your browser and the file is never uploaded.
How it works
- This runs entirely in your browser using Tesseract.js — a WebAssembly build of Google's Tesseract OCR engine. Your image is never uploaded. Most sites make you send scans to their server for this; you don't have to.
- The honest tradeoff: the language model downloads once (a few MB) on first use, and recognition is slower than a server would be — expect several seconds per page, longer on an old phone. That's the price of not uploading your documents.
- Accuracy depends heavily on input quality. Clean, straight, high-contrast scans read very well. Photos taken at an angle, blurry images, unusual fonts, and handwriting read poorly. The confidence score tells you how much to trust the output — always proofread it.
- 13 languages are supported. Pick the right one before running: OCR with the wrong language model produces nonsense.
- For multi-page PDFs, use PDF Split first, then run each page through here.
Frequently asked questions
What is OCR?
OCR stands for optical character recognition — it reads the text inside an image or scanned PDF and turns it into selectable, copyable text you can edit or search.
Are my documents uploaded to a server?
No. Text recognition runs locally in your browser, so your documents never leave your device — important for contracts, IDs, or anything confidential.
Which languages and files are supported?
It works on common image formats and PDFs. Recognition is most accurate on clear, high-contrast scans; faint or skewed pages may need a cleaner source for best results.
Why is some text recognised incorrectly?
OCR accuracy depends on image quality. Low resolution, handwriting, unusual fonts, or noisy backgrounds can cause errors — a sharper scan usually improves results.
OCR bridges pictures and text
A scanned page may look like text to a person while being only pixels to a computer. Optical character recognition analyzes those shapes and attempts to recover characters and words.
Recognition changed document search
Once text is recognized, a scanned document can become searchable and selectable. Accuracy still depends on image quality, language, typography, skew and page complexity.