The Challenge
Acme Corp, a mid-sized logistics company, was drowning in paperwork. Their team of 15 data entry specialists spent 8 hours a day manually processing invoices, bills of lading, and customs documents. Errors were common, and the backlog kept growing.
What They Tried Before
They had attempted to use traditional OCR software, but the accuracy was poor—especially with handwritten notes and varied document formats. The team spent almost as much time correcting OCR errors as they did doing manual entry.
Our Approach
We built a custom document processing pipeline using modern AI:
- Document Classification - Automatically identify document types
- Intelligent Extraction - Pull relevant data fields with context awareness
- Validation Layer - Cross-reference extracted data against existing records
- Human-in-the-Loop - Flag low-confidence extractions for review
The Technology
- Custom-trained vision models for document understanding
- Large language models for context-aware extraction
- Integration with their existing ERP system
- Real-time dashboard for monitoring and exceptions
Results After 6 Months
The system now processes over 10,000 documents daily with minimal human intervention. The data entry team has been redeployed to higher-value work, and the company saves over $200,000 annually in labor costs.
“We went from dreading the daily document pile to barely thinking about it. The system just works.” — Operations Director, Acme Corp