85% Time saving with Agentic AI for Complex Three-Way PO Matching Workflows

85% Time Savings with Automating PO, Invoice, and Receipt Matching with Agentic AI

Background & Challenge

In finance and procurement operations, three-way matching between Purchase Orders (POs), Invoices, and Receipts is a critical step in payment processing and fraud prevention. However, this matching process is often manual and time-consuming:

• POs, Invoices, and Goods Receipts come in various formats (PDFs, scans, ERP exports).
• Data fields like item codes, quantities, units, and amounts must be cross-checked across all three.
• Errors, inconsistencies, or mismatches frequently delay vendor payments or trigger compliance alerts.

The client’s AP team was overwhelmed by the volume and complexity, leading to delayed processing and high operational costs.

Solution: Agentic AI for Three-Way Document Matching

Effectz.AI developed custom Agentic AI agents designed to automate end-to-end document extraction, understanding, and matching across POs, Invoices, and Receipts.

Key Features:

• AI-Powered Document Extraction & Understanding AI Agents extracted structured data from scanned and digital POs, Invoices, and GRNs—handling variations in layout and format.
• Cross-Document Semantic Matching Items, quantities, prices, tax lines, and vendor codes were matched using rule-based and AI-driven logic.
• Bulk & 24/7 Matching Enabled round-the-clock automation, significantly reducing backlog.
• Human-in-the-Loop for Edge Cases Discrepancies were flagged for human verification with full traceability.

Results & Impact

• Up to 85% reduction in matching time
• >80% of document sets processed automatically
• Improved cash flow and vendor relationships due to faster processing
• Full audit trail for compliance and financial integrity

This solution helped the client move from manual invoice triage to a digitally intelligent workflow, improving efficiency, accuracy, and compliance readiness. It is a perfect fit for scaling in both enterprise and resource-constrained environments.