This paper presents the results of the system's implementation in real-life conditions at OFFICEMAG LLC, Russia's largest supplier of office supplies. Over an eight-week period, 12,087 documents, including applications, invoices, and certificates received from 112 suppliers, were tested. The system demonstrated 95.6% classification accuracy and 94.3% average key data extraction accuracy. The implementation reduced the processing time per document from 12 minutes to 45 seconds, significantly reduced errors, eliminated document loss, and saved 15,000 man-hours per month. Cost-effectiveness calculations showed that the system pays for itself in 1.4 days, with monthly savings of 18.3 million rubles due to reduced labor costs and the avoidance of operational losses. The results confirm that the chosen method outperforms complex ML and RPA solutions in terms of efficiency, reliability, and cost-effectiveness for large businesses.
document flow automation, regular expressions, efficiency, cost-effectiveness, logistics, 1C, OFFICEMAG LLC
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