OCR and Documents

To extract text from scanned documents, you need OCR processing to convert images to text. This skill handles non-machine-readable files like invoices and contracts, preserving page order, tables, and headings where possible to enable indexing and analysis.

Yes, OCR preserves layout, tables, and headings where possible during text extraction. It processes image-heavy files while maintaining the document's structural integrity and page order for accurate downstream processing.

The best way to digitize archival records is using OCR to convert scanned images into searchable text. This skill applies confidence-aware processing to avoid fabricating unreadable text, ensuring accurate extraction for archival workflows.

Confidence-aware text extraction flags low-confidence results instead of fabricating unreadable text. This ensures data integrity when processing scanned documents, providing transparent indicators for sections that require manual review.

Yes, you can use OCR for data ingestion from non-machine-readable contracts and forms. It converts image-based source documents into searchable text, enabling automated workflows and downstream processing for legal and administrative data.

OCR limitations include potential inability to accurately read heavily degraded or unreadable text. The skill avoids fabricating illegible characters and instead flags low-confidence areas, requiring manual verification for poorly scanned source documents.