Back to Glossary
Multimodal
OCR AI
Definition
OCR (Optical Character Recognition) AI converts text in images into machine-readable format, with modern AI-powered OCR handling complex layouts, handwriting, and multiple languages.
Why It Matters
Text appears everywhere - documents, signs, product labels, screenshots, handwritten notes. OCR is the foundational technology that makes this visual text accessible to AI systems. Modern AI-powered OCR is far more capable than traditional approaches, handling varied fonts, angles, and even handwriting.
Evolution of OCR
Traditional OCR:
- Pattern matching against character templates
- Required clean, well-formatted input
- Failed on noise, rotation, unusual fonts
Modern AI OCR:
- Deep learning-based recognition
- Handles complex layouts and mixed content
- Works with photos, not just scans
- Multilingual and multi-script support
Key Solutions
- Tesseract: Open-source, good baseline
- Google Cloud Vision: High accuracy, many languages
- AWS Textract: Optimized for documents
- PaddleOCR: Open-source, strong performance
- EasyOCR: Simple Python library
- Vision-Language Models: GPT-4o, Claude for OCR+understanding
Integration Patterns
OCR alone extracts text. For production systems, combine with: layout analysis (where is the text?), classification (what type of document?), and NLU (what does it mean?).