Special access to our historical OCR tools for researchers and educators
Get assistance from our historical document specialists for your research projects
AI Powered Advanced algorithms that go beyond OCR to understand context, meaning, and relationships within historical texts. Identify entities, detect relationships, and extract meaningful insights from your documents.
People, places, organizations
Historical date formats
Per 1000 characters
Modern & historical
Our Text Recognition technology goes beyond simple text extraction to understand the deeper meaning, context, and relationships within historical texts. Using advanced natural language processing, we identify named entities, detect temporal references, and map complex relationships.
Unlike basic OCR systems, our technology understands historical context, archaic language structures, and can distinguish between different entity types with remarkable accuracy.
We combine state-of-the-art machine learning with historical linguistic expertise to provide insights that transform how researchers work with historical documents.
"King Henry VIII granted lands in Yorkshire toThomas Cromwell in1537."
Advanced identification of multiple entity types with historical context understanding
A comprehensive six-step process that transforms unstructured text into structured insights
Upload text documents directly into the system
Auto-detect language and historical variants for context
Identify named entities with contextual understanding
Detect and map relationships between identified entities
Analyze grammatical structures and historical context
View entity networks and export structured data
Specialized features designed for intelligent text analysis and recognition
Advanced NER that identifies people, places, organizations, and historical entities
Understands historical dates, eras, and chronological relationships
Maps connections between entities including family, professional, and geographical ties
Interprets archaic language, idioms, and historical context
Works with historical and modern language variants across 180+ languages
Creates interactive entity relationship maps and timelines
How researchers and institutions are using Text Recognition
A major university used our Text Recognition to analyze 5,000+ pages of historical correspondence for a biography project. The system identified 12,000+ named entities, mapped 8,500+ relationships, and reduced research time by 75% while achieving 95.1% entity recognition accuracy.
Everything you need to know about our text recognition technology
Simple API and SDKs for all major platforms
Modern RESTful API with comprehensive documentation
Our Text Recognition achieves 95.1% accuracy for named entity recognition in historical documents. For challenging archaic language, we provide confidence scores and contextual suggestions.
Yes, our system can process documents containing multiple languages simultaneously. It automatically detects language boundaries and applies appropriate recognition models for each section.
We use contextual analysis and historical databases to resolve ambiguous references. The system provides multiple possibilities with confidence scores when references are unclear.
We support 50+ historical date formats including regnal years, religious calendars, and regional dating systems. The system can also normalize dates to modern formats for comparison.
Yes, our system allows customization of entity types and recognition rules for specific research projects. You can train custom models on your specialized documents.
Join researchers and institutions who have transformed their text analysis workflows with our advanced recognition technology
5,000 characters/month at no cost
Start analyzing in 2 minutes
Special pricing for researchers
Convert handwritten and printed documents into editable text with contextual understanding
Specialized OCR for historical printed documents and unusual typefaces
Recognize text in dozens of languages including extinct and historical variants