A scanned document is a photograph of words—not the words themselves. Until those images are converted to editable, searchable text, they cannot enter a translation workflow, populate a content management system, or support accessibility requirements. Optical character recognition is the technology that brings static documents to life in digital form.
Modern OCR engines analyze page images, detect character shapes, and map them to Unicode text with surprisingly high accuracy on clean printed sources. The output transforms locked PDFs into DOCX files, populates databases with extractable content, and makes decades of paper archives searchable. For language service providers, OCR is often the gateway service that unlocks entire project categories.
Not all OCR is equal. Simple printed documents in common languages process quickly with minimal cleanup. Complex sources—multi-column layouts, tables, mixed languages, low-quality scans, and forms with checkboxes—require advanced processing and human verification. The difference between automated-only and professionally cleaned OCR directly affects translation quality and downstream DTP effort.
Integration with translation workflows matters. OCR output should preserve document structure where possible: headings, lists, tables, and paragraph breaks. Clean, tagged text reduces pre-translation engineering time and improves CAT tool segmentation. Poor OCR dumps unstructured text that costs more to fix than the OCR itself.
Multilize offers automatic OCR with minimal manual editing for straightforward documents, scaling to comprehensive cleanup for complex sources. When your clients send scanned PDFs, OCR is where the project truly begins—and where professional handling saves time at every subsequent stage.