Scanned.to reconstructs documents from images and PDFs using specialized neural networks trained on specific document categories. Rather than just pulling text out, the system analyzes layout structures including tables, multi-column formats, headers, and design elements. It then rebuilds these documents as fully editable files where you can modify text while keeping the original formatting intact.
The OCR pipeline handles both printed and handwritten text through neural networks optimized for different document types. Legal documents get processed differently than medical records or technical manuals. This specialization improves accuracy for domain-specific terminology and formatting conventions. The system accepts PDF, JPG, PNG, and HEIC files as input.
Documents flow through the recognition layer, then into a layout reconstruction engine. This second stage maps spatial relationships between text blocks, images, and structural elements. The output comes in three formats: editable Word documents, searchable PDFs, or shareable web pages. Each format maintains the original layout structure.
Translation works across 50+ languages while preserving formatting. The system does not just translate text strings. It maintains table structures, column alignments, and header hierarchies in the target language. This matters for contracts, invoices, and research papers where layout conveys meaning.
All files get encrypted during transmission and storage. The service explicitly doesn't use uploaded documents for training AI models. For developers, there's API access to integrate the OCR and translation capabilities into custom workflows. You can build document processing pipelines or automated translation systems.
The free tier works for basic use. Free uploads get automatically deleted after 24 hours, which limits it for archival purposes. You can't keep documents long-term without paying. No information about paid plan pricing or features is publicly detailed.
Reading analytics track how people interact with shared documents. You'll see who opened what and when. The sharing system generates secure links for distribution.
The main technical limitation is the 24-hour retention window for free users. This makes it impractical for building a document library or maintaining historical records. You'd need to re-upload files each time. The service doesn't offer mobile apps or browser extensions, so access happens through the web interface or API only.
The document-type-specific neural networks set this apart from generic OCR tools that treat every document the same way. A medical report gets processed with different recognition patterns than a legal brief. This specialization improves accuracy but means the system needs to correctly identify document types first.
