AI and Transport: Automated Document Reading
Category: Features Author: Baudouin de Dreuille Date: 3/6/2025 Reading time: 2 min
A closer look at the use of AI in transport and logistics through a concrete use case: automated document reading.
In practice, OneChain uses AI to automatically read carrier rate sheets and quotes as well as their invoices.
Automated document reading relies on Optical Character Recognition (OCR) and Natural Language Processing (NLP). Combined with machine learning, these technologies enable the extraction, analysis, and structuring of key information from documents:
- OCR extracts raw text from physical or scanned documents.
- NLP analyzes this text to derive contextual information, detect patterns, or interpret more complex elements.
- Machine learning applied to OCR and NLP enables the decoding of non-standardized documents as well as the most complex ones.
Example: Automated Invoice Reading on OneChain
Step 1: Invoice Extraction
OCR, enhanced by machine learning, extracts data even when the invoice is in a non-standard format. Machine learning applied to OCR and NLP enables the decoding of non-standardized documents as well as the most complex ones.
Step 2: Content Understanding
NLP, powered by machine learning, automatically identifies critical fields.
Step 3: Verification
A machine learning model compares the invoice against the quote or pre-billing document (line by line).
Step 4: Automation
If everything checks out, the invoice is automatically validated and integrated into the accounting system. Otherwise, a review workflow is triggered.