Scanned documents — invoices, contracts, medical forms, ID cards — are some of the most sensitive files people feed into AI tools. But most OCR services require uploading your image to a server. Here's how to extract and clean text from scans without exposing the content.
The hidden risk of cloud OCR
When you upload a scanned contract to an online OCR tool, you're sending:
- The full image (including signatures, letterheads, and handwritten notes)
- Any PII visible in the scan (names, addresses, account numbers)
- Structural information about the document (headers, layouts, stamps)
Many OCR services retain uploaded images for "quality improvement." Some add them to training datasets. Even services that promise deletion may have retention windows of 24-72 hours.
For sensitive documents — legal contracts, medical forms, financial statements — this is unacceptable.
Browser-based OCR: how it works
CleanMyPrompt's image-to-text tool uses Tesseract.js, a WebAssembly port of the Tesseract OCR engine. The entire process runs in your browser:
- File stays local: The image is loaded into browser memory via the File API. No HTTP upload occurs.
- WebAssembly processing: Tesseract.js runs the OCR model in a Web Worker, using your CPU — not a remote server.
- Text output in DOM: The extracted text appears in the output panel. It exists only in browser memory.
- No network activity: Verify by opening the browser's Network tab during processing. Zero requests are made with your image data.
The OCR-to-AI pipeline
Extracting text is only step one. Before sending OCR output to an AI tool, you need to clean it:
Step 1: Extract text from the image
Drop your scanned PDF, JPG, or PNG into the image-to-text tool. The OCR engine extracts readable text.
Step 2: Fix formatting artifacts
OCR output is notoriously messy — broken line breaks, random spaces, page numbers, headers repeated on every page. Run the text through the PDF cleaner to fix formatting.
Step 3: Redact PII
Scanned documents often contain dense PII: names at the top, signatures at the bottom, account numbers throughout. Enable Auto-Redact to strip emails, SSNs, phone numbers, and other identifiers.
Step 4: Compress tokens (optional)
If you're sending the text to a paid API, use Squeeze Mode to reduce token count by 30-40%. This is especially useful for long scanned documents where OCR adds verbosity.
Step 5: Copy cleaned text to AI
The result is clean, formatted, PII-free text that you can safely paste into ChatGPT, Claude, or any LLM.
Common document types and their risks
| Document Type | PII Present | Recommended Cleaning |
|---|---|---|
| Invoices | Company names, addresses, account numbers | Redact names + addresses |
| Contracts | All parties' names, addresses, dates, signatures | Full PII redaction |
| Medical forms | Patient name, DOB, SSN, diagnoses | Full redaction + manual review |
| ID cards | Name, photo, ID number, address | Do not process — too sensitive for AI |
| Bank statements | Account numbers, transactions, balances | Full redaction |
| Receipts | Partial card numbers, merchant info | Redact financial data |
OCR accuracy tips
Tesseract.js works best with:
- High-resolution images (300 DPI or higher)
- Clear, dark text on light background
- Minimal skew (straighten the scan before processing)
- Latin-script text (English, Spanish, French, German — Tesseract supports 100+ languages but accuracy varies)
For low-quality scans, consider:
- Increasing contrast before OCR
- Cropping to the text area only
- Processing one page at a time for multi-page documents
Why self-hosted OCR matters for compliance
Under GDPR, processing scanned documents containing personal data requires appropriate technical measures. Running OCR client-side satisfies this because:
- No data transfer: Article 28 processor requirements don't apply when processing is local
- No retention risk: The image is never stored on external servers
- User control: The data subject (or data controller) retains full control throughout
For organizations audited under ISO 27001 or SOC 2, browser-based OCR simplifies the documentation — there's no third-party processor to assess.
Try it
Upload a scanned document to the image-to-text tool, then chain it with PII redaction and token compression. The entire pipeline runs in your browser — verify by watching the Network tab.