You receive a 30-page contract faxed by an old-school client. Impossible to search a keyword, impossible to copy-paste a paragraph. You'd have to retype the whole thing.
This is exactly what OCR (Optical Character Recognition) solves. In 2026, recognition quality is such that a properly OCR'd scan is indistinguishable from a native PDF — for search, copy-paste, archiving, indexing.
Here's how it works, when to use it, and how to choose between the many solutions.
Why OCR has become indispensable
If you work in any of these fields, you probably already OCR without knowing it:
- Law firm: find a specific clause in old contracts
- Accounting: index 10 years of scanned invoices per client
- HR: make CVs received as non-editable PDFs searchable
- Notary: digitize old deeds kept in archive
- Academic research: cite passages from scanned books
Without OCR, these documents are images. They contain no "text" from a computer's standpoint. With OCR, they become text — indexable, copyable, translatable, editable.
How modern OCR works
Older OCR (until the 2010s) relied on shape recognition: each character is compared to a known shape library. Average accuracy, especially on slightly tilted scans or unusual fonts.
Modern OCR (Tesseract 5+, Google Vision, AWS Textract, etc.) uses convolutional neural networks (CNN) trained on tens of millions of pages. The model no longer recognizes isolated characters but understands context: an ambiguous "rn" will be read "rn" if the word is "morning" but "m" if it's "men."
Typical accuracy on a clean A4 scan at 300 DPI:
- Typed documents in French/English: 99.5%+
- Neat handwriting: 85-95% (with specific training)
- Free handwriting: 60-80% (still OCR's Achilles heel)
- Decorative fonts: variable, sometimes poor
- Complex tables: structure often lost, text generally good
Local vs server: choosing architecture
For a firm or SMB, the OCR architecture choice has real implications.
Browser OCR (Tesseract.js)
Pros:
- No data leaves the machine
- Maximum confidentiality
- No recurring cost
Cons:
- Slow: 3-10 seconds per page on a modern machine
- Limited to lightweight models (~95% accuracy instead of 99%)
- Unsuitable for PDFs over 50 pages
- Drains battery (intensive computation)
Relevant for: occasional OCR on 1-5 pages, very sensitive data.
Server OCR (cloud models)
Pros:
- Very fast: 0.2-1 second per page
- Top-tier models (99.5%+ accuracy)
- Multilingual (60+ languages)
- Structured table recognition
- No load on the client machine
Cons:
- Files transit through a server
- Recurring service cost
- Connection-dependent latency
Relevant for: bulk processing, high accuracy requirement, multilingual.
What's PDFly's choice?
PDFly's OCR tool is coming soon, and it was designed around the following choice: server processing on our servers in Paris (EU), files deleted immediately after processing, and free to use — with fair-use limits, because every OCR job takes real computing power on our servers.
Why not in-browser? Because Tesseract.js accuracy (~95%) isn't enough for professional uses where every error costs proofreading time. Server models (99.5%+) eliminate that cost.
Why in Europe? For the same reasons our Cloud Act article details: legal contracts, HR files, and invoices have no business on US servers.
How to OCR a PDF with PDFly (coming soon)
PDFly's OCR isn't available yet. When it launches, it will add an invisible text layer to your scanned PDF: the document stays visually identical to the original, but becomes searchable and copyable. Like every PDFly tool, it will be free, with no sign-up.
Want to know when it's ready? Leave your email on the OCR tool page and we'll let you know at launch.
In the meantime, if you're comfortable with a terminal, the open-source OCRmyPDF (built on Tesseract) does the job locally, on your own machine:
ocrmypdf -l eng scan.pdf searchable.pdf
Good to know: an OCR'd PDF typically weighs 5-15% more (the text layer adds weight). If size matters, compress the result afterward.
Common pitfalls and how to avoid them
Scan pitfalls
- Tilted scan: text 5° off-axis drops OCR accuracy from 99% to 70%. Many tools auto-correct ("deskew"), but not all. Check for it.
- Low-resolution scan (<200 DPI): degraded accuracy. Re-scan at 300 DPI minimum.
- Scan with gray/yellow background (old photocopies): apply a white threshold before OCR.
- Black on blue/green background: insufficient contrast. Convert to grayscale first.
PDF pitfalls
- Protected PDF: OCR often blocked. Remove the password first if you're authorized — PDFly's Unlock tool is coming soon, free as well.
- Already partially OCR'd PDF: some pages have text, others don't. Re-OCR'ing the entire document is simpler than processing only some pages.
- PDF with complex columns: reading order can be incorrect (reads column 1 line 1 then column 2 line 1 instead of all of column 1). For scanned newspapers and magazines, expect some manual rework.
Legal pitfalls
- OCR on a signed document: the text layer doesn't modify the image, so the signature remains valid. But some courts refuse a re-processed PDF after signing. Check local legal context.
- Probative archiving: if you archive an OCR'd version for evidentiary value, also keep the original non-OCR'd file (eIDAS requires traceability of the transformation).
Concrete use cases
Law firm
Index 10 years of jurisprudence received as scanned PDFs. Bulk OCR, then full-text search in the firm's DMS. Gain: find a specific clause in 5 seconds instead of 3 hours.
Accounting firm
Digitize client invoices received on paper or low-quality scans. OCR with table extraction, then import into accounting software (Cegid, Sage, etc.). Gain: automate journal entries.
HR
Make a base of 5,000 CVs received over 5 years searchable. OCR + Elasticsearch indexing. Gain: find "Java + 5 years + Bordeaux" in 1 click.
Academic research
Digitize an out-of-copyright rare book for citation. Multilingual OCR, export to TXT, copy-paste into thesis with citations.
In summary
Modern OCR has become a reliable technical commodity. The tool choice mostly depends on required confidentiality and volume.
For daily firm/accounting/HR documents: EU server OCR offers the best accuracy/speed/GDPR-compliance compromise. That's exactly what PDFly's upcoming OCR will be — and it will be free.
Get notified when PDFly's OCR launches — free, processed in Europe, files deleted immediately after.