AI-Powered Invoice Processing System
Deploys 8 specialized AI agents in a phase-based orchestration pipeline simulating enterprise AP automation. Document ingestion classifies and prepares invoices, extraction agents use OCR/NLP to capture data fields, validation agents verify against master data, matching agents perform three-way reconciliation, fraud detection analyzes patterns, approval routing applies DoA matrix, GL coding assigns accounts, and payment preparation optimizes timing for discounts.
Problem Statement
The challenge addressed
Solution Architecture
AI orchestration approach
Invoice Selection Interface - Multi-vendor invoice batch selection showing 5 invoices worth $168,000 from vendors including Boston Consulting Group, AT&T Business, Workday Inc, with batch configuration, priority levels, and processing estimates
AI Agent Orchestration Document Ingestion - Real-time processing phases showing Document Ingestion at 92.1% confidence with receive, classify, quality assessment, and pre-processing steps completed, live agent reasoning and decision logs
Invoice Processing Results Dashboard - Completion summary showing 5 invoices worth $168,000 processed in 30 seconds with 96.3% extraction accuracy, executive summary highlighting high OCR accuracy and automated approvals with $1,008 estimated cost savings
Process Summary Workflow Timeline - Complete 5-stage pipeline visualization from Invoice Upload & Data Extraction through Validation & Matching, Orchestration & Rule Processing, Decision Synthesis to Results & Reporting, showing 30s duration with 6 agents and 96.3% accuracy
AI Agents
Specialized autonomous agents working in coordination
Document Ingestion Agent
Invoices arrive in multiple formats (PDF, image, EDI) with varying quality. Manual document sorting and preparation creates bottlenecks and delays downstream processing.
Core Logic
Receives and classifies invoice documents by format type, performs quality assessment for image readability scoring, and executes pre-processing including orientation normalization and contrast enhancement. Prepares documents for optimal OCR extraction with automated format detection and routing.
AI Data Extraction Agent
Manual data entry from invoices is slow, error-prone, and expensive. Extracting vendor names, amounts, dates, line items, and tax information from unstructured documents requires significant human effort.
Core Logic
Applies OCR processing to extract raw text, performs layout analysis to understand document structure and zones, executes entity extraction to identify vendor, amounts, dates, and line items using NLP. Normalizes data formats (dates, currencies, addresses) and calculates confidence scores per field. Achieves 96.3% average extraction confidence with all critical fields above 98%.
Data Validation Agent
Extracted invoice data may contain errors, invalid vendor IDs, incorrect tax calculations, or duplicate submissions. Without validation, erroneous invoices proceed through the workflow causing payment failures and reconciliation issues.
Core Logic
Performs vendor master lookup to verify existence in ERP, validates tax identification numbers against IRS database, executes mathematical validation to verify line item totals and calculations, checks invoice date reasonableness, and detects duplicate invoice submissions across 90-day lookback period. Generates validation scores and auto-fixable issue recommendations.
Three-Way Matching Agent
Reconciling invoices against purchase orders and goods receipts is labor-intensive and error-prone. Price and quantity variances require investigation, and mismatched documents delay payment processing.
Core Logic
Searches for matching purchase orders by number or content analysis, matches invoice lines to PO lines with confidence scoring, locates corresponding goods receipts, verifies received quantities, calculates price and quantity variances, and applies configurable tolerance thresholds. Reports 98.7% PO match confidence with variance analysis for discrepancies outside tolerance.
AP Fraud Detection Agent
Invoice fraud including duplicate payments, phantom vendors, and inflated amounts costs organizations billions annually. Rule-based systems miss sophisticated fraud patterns while generating excessive false positives.
Core Logic
Analyzes invoices for known fraud patterns, performs velocity checks on invoice submission frequency, detects unusual amounts compared to historical baseline, evaluates vendor risk profiles, and calculates ML-based fraud probability scores. Identifies high-risk invoices for enhanced review before payment authorization.
Approval Routing Agent
Manual approval routing is slow and inconsistent. Determining appropriate approvers based on amount thresholds, expense categories, and delegation rules requires knowledge of complex organizational policies.
Core Logic
Performs Delegation of Authority (DoA) matrix lookup to determine required approval levels, identifies appropriate approvers based on amount and category, checks for active delegations, evaluates auto-approval eligibility against thresholds ($10,000 limit), and assigns invoices to appropriate approval workflow queues. Supports multi-level approval chains.
GL Coding & Allocation Agent
Assigning general ledger accounts, cost centers, and tax codes to invoices requires accounting expertise and is time-consuming. Incorrect coding leads to financial reporting errors and audit findings.
Core Logic
Classifies expense type categories, assigns appropriate chart of accounts codes, allocates to cost centers based on purchase order or invoice content, assigns tax codes with correct rates, and handles multi-entity intercompany allocations. Uses historical patterns and vendor mappings for high-confidence coding recommendations.
Payment Preparation Agent
Treasury teams miss early payment discounts due to manual processing delays. Verifying vendor bank details for each payment is time-consuming, and payment file preparation requires coordination across multiple systems.
Core Logic
Determines optimal payment date based on payment terms (2/10 Net 30), identifies early payment discount opportunities with savings calculation, verifies vendor bank account details, assigns invoices to payment batches, and completes payment file preparation for ERP export. Captures early payment discounts averaging 2% ($900 on $45K invoice).
Worker Overview
Technical specifications, architecture, and interface preview
System Overview
Technical documentation
Tech Stack
5 technologies
Architecture Diagram
System flow visualization