Explore Logistics Automation
Glossary Terms

Handle the changing environment of logistics automation with confidence. Our comprehensive glossary simplifies technical terms and offers precise definitions to help you prepare your company for the future. Learn the language that promotes efficiency and creativity, from the basics of automation to more complex ideas.

Optical Data Recognition AI

Last updated: October 30, 2025
Logistics Automation
O

Optical Data Recognition AI refers to the use of artificial intelligence and computer vision to extract printed or handwritten information from physical logistics documents. These can include delivery receipts, customs forms, invoices, or packing slips. Unlike traditional OCR, which works best with printed text, this AI-powered solution is capable of recognizing irregular handwriting, smudged characters, and multi-language content with greater accuracy and speed.

How Optical Data Recognition AI operate?

Using high-resolution scanning devices or mobile cameras, logistics teams capture images of documents. Optical Data Recognition AI processes these images through machine learning models trained on diverse fonts, scripts, and layouts. It identifies text blocks, recognizes characters, and converts them into structured digital data. The system then validates this information against predefined fields, like shipment numbers, names, or delivery addresses, and forwards it into ERP or TMS platforms for real-time processing and analysis.

Key Capabilities of Optical Data Recognition AI

Handwritten Text Recognition

Accurately deciphers handwritten signatures, annotations, and numbers commonly found on paper-based delivery notes.

Multi-Language Support

Supports recognition of diverse languages and regional scripts, enhancing global logistics compatibility.

Error Reduction in Data Entry

Minimizes mistakes caused by manual typing, improving accuracy in shipping records and billing.

Integration with Logistics Systems

Extracted data is directly synced with ERP, WMS, or CRM tools for instant availability and use.

Time-Efficient Document Handling

Speeds up data capture from piles of physical documents, saving hours of manual entry work.

Conclusion

Optical Data Recognition AI transforms the way logistics teams manage physical documents by digitizing handwritten and printed content with high accuracy. It simplifies data processing, reduces errors, and accelerates administrative workflows across global supply chains. For logistics companies handling bulk paperwork, this technology ensures fast, reliable, and intelligent document processing.