Invoice Automation Agent

Overview

Built an AI agent that reads invoices in any format, matches them against the ERP system, flags anomalies, and routes approvals. The agent learns from corrections and improves over time...

The Problem

A mid-size logistics company was drowning in invoice processing. Three staff members spent their days manually extracting data from PDFs, matching invoices to purchase orders, and flagging discrepancies. Error rates were climbing. Morale was not.

The Solution

Built an AI agent that reads invoices in any format, matches them against the ERP system, flags anomalies, and routes approvals. The agent learns from corrections and improves over time.

Architecture

• Document ingestion pipeline with OCR and layout analysis
• LLM-powered extraction with structured output validation
• Fuzzy matching engine for PO reconciliation
• Anomaly detection with confidence scoring
• Human-in-the-loop approval workflow
• Integration layer for ERP sync

Business Impact

• Reduced processing time from 3 days to 4 hours
• Cut error rate from 12% to under 1%
• Freed up 3 FTEs for higher-value work
• ROI positive within 8 weeks

Lessons Learned

• Document layouts vary wildly - invest heavily in preprocessing
• Confidence thresholds need tuning per document type
• Human review UX determines adoption more than accuracy
• Start with the messiest documents first

Next Steps

• Multi-currency support
• Automated payment scheduling
• Vendor anomaly detection