A Gulf telecom operator's finance function - Multimodal invoice validation
Telecommunications / Finance · Gulf
شكل هذه المشكلة
A human reads it and types it in again
المشكلة
AP teams were manually comparing supplier PDFs, iSupplier entries, and Oracle ERP records. Three-way matching is the kind of work that is too rule-bound to be interesting and too variable to script: the same supplier's invoice arrives in a different layout each quarter, and the discrepancies that matter are small ones buried among formatting differences that do not. Because the check was manual it was also quietly sampled under load - which is exactly when errors are most likely.
ما بنيناه
We used a multimodal vision model and a managed model platform to extract invoice fields, reconcile all three sources, flag mismatches, and support correction notifications back to the supplier.
ما تغيّر
| المقياس | قبل | بعد |
|---|---|---|
| Invoices reconciled across supplier PDF, iSupplier and ERP | a sample under load | 100% |
| Average validation time per invoice | 12 minutes | 45 seconds |
| Repeat mismatches from the same supplier after correction notices | † | down 67% |
† مقيسة مقابل المستوى السابق للمقياس نفسه.
Average validation time per invoice
Repeat mismatches from the same supplier after correction notices
مقيس مقابل عملية العميل السابقة نفسها، مُقاسة إلى ١٠٠. والمصدر ينشر مقدار التغيّر، لا الرقم المطلق الذي تغيّر عنه.
الأرقام من سجلات التنفيذ الخاصة بالممارسة للمشروع المذكور، مقيسةً مقابل العملية التي سبقته.
ما توقّف عليه
Closing the loop back to the supplier is what stopped the same mismatch recurring every month - detection alone would have relocated the work rather than removed it. Relevant to finance operations whose control is technically three-way matching and practically a sample.
- خط الخدمة
- AI Document Intelligence
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