Enterprises frequently face mismatches between purchase orders and invoices, leading to overbilling, duplicate payments, and delayed reconciliation. Legacy OCR-based systems can extract data but lack the intelligence to perform accurate line-item matching, forcing finance teams to manually validate items, quantities, and pricing across documents. This manual effort increases operational costs and exposes organizations to financial risk.
AI-powered PO-invoice matching automates validation by extracting and comparing structured data from invoices and purchase orders. By detecting mismatches and overbilling proactively, organizations reduce payment errors, accelerate invoice approvals, and improve procurement compliance.
This total cost of ownership calculator helps you evaluate the true ROI of the category using modern AI powered alternatives over traditional OCR based solutions.
PO-Invoice Matching
Validates invoices against purchase orders by comparing items, quantities, and prices to detect mismatches or overbilling.
Start by selecting a typical scenario or adjust the baseline details to reflect your exact needs. The calculator will update automatically.
Legacy OCR solutions achieve 80% accuracy and lack the ability to perform reliable line-item validation. Finance teams must manually review invoice and purchase order data, leading to high processing costs, longer reconciliation cycles, and increased risk of errors.
Modern AI combining OCR, NLP, and rules-based matching achieves 92% accuracy ±2% in validating POs against invoices. While this reduces manual workload significantly, AI cannot fully guarantee detection of complex line-item discrepancies, requiring finance teams to perform targeted verification before final approvals.
Your AI investment isn’t delivering expected savings. This may indicate inefficiencies or incorrect assumptions in your current workflow.
Contact us to identify more optimization opportunities.
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