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Transkribus – AI-Powered Document Transcription & Digitization Platform

Transkribus is an AI-powered platform that converts handwritten and printed documents into searchable digital text using advanced text recognition models. It enables researchers, archives, and institutions to digitize and analyze historical records efficiently.

Flutter Django FastAPI React MongoDB

Problem Statement

Historical documents and handwritten records are difficult to read, search, and analyze manually. Traditional OCR tools fail to accurately interpret complex handwriting styles, making large-scale digitization slow, costly, and inefficient.

Project Objective

To develop an AI-driven platform that automates transcription of handwritten and printed documents, enables custom model training, and transforms static archives into structured, searchable digital data for research and analysis.

High Fidelity Screens

Screen Screen Screen

Key Features

AI Text Recognition (HTR + OCR)

Automatically converts handwritten and printed documents into editable text across 100+ languages with high accuracy.

Custom AI Model Training

Users can train AI models tailored to specific handwriting styles or document formats, improving recognition accuracy over time.

Layout & Data Extraction

Advanced layout detection extracts structured data like tables, fields, and document regions for better analysis and usability.

Search, Collaboration & Publishing

Users can annotate, tag, search, and publish digitized collections online, making archives accessible globally.

Development Process

1

Discovery Phase

Identified major challenges in digitizing historical and handwritten documents. Studied limitations of traditional OCR systems. Defined need for

2

Design Phase

Designed user-friendly web interface with document workspace (Desk, Models, Sites). Created workflows for upload → recognition → editing → publishing. Focused on accessibility for researchers and non-technical users

3

Development Phase

Built AI pipelines for handwriting recognition (HTR) and printed OCR. Developed APIs for integration with external systems. Implemented modular tools for tagging, editing, and data extraction

4

Testing Phase

Tested accuracy across multiple languages and handwriting styles. Validated performance on large datasets (millions of pages). Conducted usability testing with researchers and institutions

5

Deployment

Deployed as a cloud-based SaaS platform. Ensured GDPR-compliant infrastructure and secure data handling. Enabled large-scale processing (millions of documents globally)

Technology Stack

Frontend

  • React
  • TypeScript
  • Tailwind CSS
  • Redux

Backend

  • Python
  • Django
  • Django REST Framework
  • Celery

AI/ML

  • Natural Language Processing (NLP)
  • Machine Learning Models for personality scoring
  • Video & text analysis algorithms

Database

  • PostgreSQL
  • Redis
  • Elasticsearch

Infrastructure

  • AWS EC2
  • AWS S3
  • Docker
  • Kubernetes

DevOps

  • CI/CD Pipeline
  • GitHub Actions
  • Monitoring Tools

Results & Impact

After deploying Transkribus, institutions and researchers were able to digitize massive collections of historical documents that were previously inaccessible due to handwriting complexity. The platform significantly reduced manual transcription effort and enabled searchable, structured datasets from scanned archives. This transformation improved research efficiency, collaboration, and accessibility of cultural heritage worldwide.
80%
Faster Document Transcription
50K+
Pages Processed
92%
Recognition Accuracy (with trained models)
65%
Reduction in Manual Workload

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