[Case Study] - Asia F&B Group Cuts Document Processing Time by 65% with AI
An Asia-based multinational F&B group validated an Intelligent Document Processing System using Knotest before committing. A one-month A/B test slashed processing time by 65.3%, boosted throughput by 188.5%, and cut error rates by 69.6%. Operations manager Mr. Lee: “Once you see the data, the choice is obvious. This isn’t just faster — it’s more reliable.”
Processing supplier invoices, delivery orders and credit notes had become a major bottleneck for an Asia-based multinational F&B group. Poor scans, stamps covering text, and inconsistent formats made the work slow and error-prone.
“Most of the time, our team was just typing, checking, re-checking,” said operations manager Mr. Lee. “When documents looked different or scans were bad, everything slowed down. Errors would slip through.”
Before committing to an AI solution, the group turned to Knotest, developed by Hephaknot, to validate the decision with real data.
First, they ran a model performance test targeting tough scenarios: poor scan quality, stamp obstructions and inconsistent formats. The Intelligent Document Processing System passed. Next came a one-month A/B Business Impact Assessment, with Group A using manual processing and Group B the AI system.
The results were clear:
- Average Processing Time per Document: (−65.3%)
- Documents Processed per Hour: (+188.5%)
- Document Processing Accuracy: (+10.6%)
- Error Rate: (−69.6%)
- Daily Manual Workload (Team): (−32.6%)
“Once you see the data, the choice is obvious,” Mr. Lee said. “This isn’t just faster — it’s more reliable. Our team can focus on what actually matters now.”