Autonomous Multi-Agent Procurement & Invoice Reconciliation Engine
A production demonstration of four autonomous LangGraph agents that extract unstructured PDF line items, verify quantities in SAP ERP schemas, isolate discrepancy variances, and generate GL accounting ledger entries with human review only on high-value outliers.
Identifying the Core Problem
Supply chain enterprises process complex, unstructured supplier invoices each month. Manual accounts payable workflows require staff to cross-reference document line items against purchase order tables, creating processing bottlenecks and error vulnerabilities.
How OXELVO Solved It
OXELVO engineered a deterministic multi-agent state machine. Agent 1 parses and normalizes OCR layout data. Agent 2 checks purchase orders in the ERP. Agent 3 evaluates price and quantity variance thresholds. Agent 4 prepares atomic ledger commits while routing variances to human reviewers via an approval portal.
Key System Features
- Layout-aware document OCR parsing extracting 40+ tabular invoice fields
- LangGraph state machine graph with checkpoint persistence against system interruptions
- Deterministic Pydantic schema validation preventing erroneous transaction commits
- Human-in-the-loop (HITL) exception escalation dashboard with webhook callbacks
- Automated vendor notification sequences for missing documentation
Engineering Decisions & Guardrails
This project represents an active technical demonstration and architectural blueprint engineered by OXELVO. We share code blueprints, schemas, and live demonstrations to verify real-world feasibility before client commercialization.
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