Upload a photo or scan. Get readable text in seconds.
Any handwriting style100+ languagesFree to try
This demo uses Text Titan, our most powerful AI model. Create a free account to get 50 credits every month - no credit card required.
500 000+
Users worldwide
200+ Million
Pages processed
300+
Public AI Models
100+
Languages supported
How it works
AI trained on millions of handwritten pages
Text Titan I, our flagship AI model, was trained on more than 30 million words from historical documents spanning multiple centuries and languages. The AI analyzes the shape and flow of each letter, learning to recognize patterns even in difficult handwriting. It processes your document line by line, converting handwritten strokes into digital text.
Works with cursive, Kurrent, Fraktur, and historical scripts
300+ public models for different handwriting styles and languages
Processes photos from your phone or high-resolution scans
The demo above gives you a taste. The full Transkribus platform lets you process thousands of pages, train custom AI models on your specific handwriting, search across all your documents, and export in any format you need.
Train custom models on your specific handwriting or script
Full-text search across all your transcribed documents
Transkribus handles a wide range of handwritten materials. Whether you have old family letters, historical manuscripts, church records, or research notes - the AI adapts to different handwriting styles and document types.
Handwriting recognition (also called HTR - Handwritten Text Recognition) uses deep learning neural networks to convert images of handwritten text into machine-readable characters. Unlike OCR for printed text, HTR must handle the infinite variation in human handwriting - different letter shapes, connected strokes, and personal styles.
Neural networks trained on millions of handwritten samples
Layout analysis detects lines and text regions automatically
Character-level recognition handles connected and cursive writing
Language models improve accuracy by understanding word context