In today's digital business environment, accounts payable departments face mounting pressure to process invoices faster, more accurately, and with fewer resources. At Artificio, we've developed a sophisticated purchase order matching system that transforms this traditionally manual process into a streamlined, automated workflow. This post explores how our system works, the technology behind it, and the real business benefits it delivers.

The Problem with Traditional PO Matching

Before we dive into our solution, let's understand why traditional PO matching is so challenging:

Traditional invoice processing typically involves manually comparing information across multiple documents:

• Checking that the PO number on the invoice matches a valid purchase order

• Verifying that invoice amounts match the PO amounts

• Confirming that the vendor information is consistent

• Reconciling line items across documents

• Ensuring dates make logical sense (PO created before invoice)

This process is:

• Time-consuming: Each invoice can take 10-15 minutes to process manually

• Error-prone: Manual data entry and comparison introduces mistakes

• Inconsistent: Different staff may apply different standards for what constitutes a "match"

• Difficult to scale: As invoice volumes grow, so does the need for staff

• A bottleneck: Delayed invoice processing affects vendor relationships and misses early payment discounts

Artificio's Two-Dataview Approach to PO Matching

Our approach fundamentally rethinks how document data is processed and compared, using separate dataviews with an intelligent matching system. Let's break down how it works:

Step 1: Specialized Document Extraction

Rather than using a one-size-fits-all approach, we've built dedicated extraction models for each document type:

Invoice Extraction Model

• Processes incoming invoices

• Identifies and extracts key fields (PO number, vendor, amounts, line items)

• Validates mathematical consistency (line items add up to totals)

• Stores structured data in the Invoices dataview

PO Extraction Model

• Processes purchase orders

• Extracts authorized amounts, approved vendors, line items

• Captures approval information and terms

• Stores structured data in the PO dataview

This specialization allows each model to achieve much higher accuracy than generic extraction systems. Our models understand the specific layouts, terminology, and validation rules for each document type.

Step 2: Structured Data Storage in Dedicated Dataviews

Extracted data is organized into two key dataviews:

This structured approach allows for precise field-by-field comparison while maintaining complete document lineage.

Step 3: Intelligent Cross-Dataview Matching

Here's where the real magic happens. Our matching engine uses a sophisticated process to compare records across the two dataviews:

Matching Process Flow:

1.  For each incoming invoice in Invoices dataview:

├── Extract PO number reference

├── Search PO dataview for corresponding record

└── If PO found, proceed to detailed comparison

2.  Field-by-field comparison:

├── Compare vendor names (allowing for minor variations)

├── Compare total amounts (within configurable tolerance)

├── Compare line items (descriptions, quantities, unit prices)

└── Check date sequence (PO date should precede invoice date)

3.  Calculate weighted match score:

├── PO Number match: 40% of score

├── Amount match: 30% of score

├── Vendor match: 20% of score

└── Line item match: 10% of score

4.  Apply business rules:

├── If match_score ≥ 95% and no critical issues: flag="Clean"

├── If PO not found: flag="No_PO_Match"

├── If amount differs > 1%: flag="Amount_Mismatch"

├── If line items don't align: flag="Line_Item_Mismatch"

├── If invoice date before PO date: flag="Date_Issue"

└── If multiple potential PO matches: flag="Multiple_PO_Match"

5.  Update invoice record with results:

├── Set match_score field

└── Set flag field

This process combines rule-based logic with weighted scoring to provide nuanced matching that goes beyond simple yes/no determinations.

Step 4: Automated Workflow Routing

The match results drive automated approval workflows:

• Invoices with match_score > 95% and flag="Clean" are automatically approved

• Others are routed to appropriate personnel based on the exception type

• For example, "Amount_Mismatch" flags might go to purchasing, while "No_PO_Match" goes to accounts payable

This intelligent routing ensures that each exception is handled by the right person, accelerating resolution and maintaining control.

The Technology Behind Our Solution

Our system combines several cutting-edge technologies:

Document Processing Technology

• OCR+: Advanced optical character recognition enhanced with machine learning for improved accuracy on complex documents

• Layout Analysis: Sophisticated algorithms that understand document structure beyond simple text extraction

• Data Validation: Built-in consistency checks that validate extracted information (e.g., checking that line items sum to totals)

Matching Intelligence

• Fuzzy Matching: Algorithms that accommodate minor variations in text fields (e.g., "Acme Inc." vs "Acme Incorporated")

• Configurable Tolerances: Customizable thresholds for numerical comparisons (e.g., accepting a 1% variance in amounts)

• Weighted Scoring: Sophisticated scoring that prioritizes critical fields while considering all available information

System Architecture

• Microservices Design: Modular components that can scale independently to handle volume fluctuations

• API-First Approach: Extensive APIs that enable integration with ERPs, accounting systems, and procurement platforms

• Event-Driven Processing: Real-time processing triggered by document arrival events

Real-World Results: Before and After

Organizations implementing our PO matching solution see dramatic improvements across key metrics:

These improvements translate directly to bottom-line impact through reduced labor costs, early payment discount capture, and improved cash flow management.

Beyond Basic Matching: Advanced Capabilities

Our system extends beyond simple invoice-to-PO matching to provide additional value:

Three-Way Matching

When goods receipt information is available, our system can perform three-way matching:

Three-Way Matching Flow:

 Invoice ─┐

├─ Compare quantities, items, dates ─► Match determination PO ──────┤

│ Receipt ─┘

This ensures that payment is only authorized for goods that have actually been received, adding another layer of control.

Partial Matching for Split Deliveries

Our system handles complex scenarios like split deliveries:

Split Delivery Handling:

The system tracks the cumulative quantities against the original PO, ensuring that the total invoiced never exceeds what was authorized.

Recurring Invoices with Contract Validation

For subscription services or recurring charges, our system can validate against contract terms stored in the PO dataview:

Contract Validation:

This capability is particularly valuable for services that don't have associated goods receipts but still require validation against authorized spending.

Implementation and Integration

Implementing Artificio's PO matching solution is straightforward:

1.  Assessment: We analyze your current process, document types, and exception patterns

2.  Configuration: We customize matching rules, tolerances, and workflows to your requirements

3.  Integration: We connect with your existing systems (ERP, accounting software, document management)

4.  Validation: We run parallel processing to verify accuracy before full deployment

5.  Training: We train your team on exception handling and system administration

6.  Go-Live: We transition to the automated workflow with careful monitoring

Typical implementation timeframes range from 4-8 weeks, depending on the complexity of your document types and integration requirements.

The Evolution of Your AP Process

As organizations implement Artificio's solution, their accounts payable function evolves:

This evolution transforms accounts payable from a transaction-processing cost center to a strategic function that contributes valuable financial insights.

Conclusion: The Future of Invoice Processing

Artificio's intelligent PO matching system represents the future of invoice processing a future where manual data entry and comparison are replaced by intelligent automation that not only reduces costs but also improves control and generates business insights.

By leveraging specialized extraction models, structured dataviews, and sophisticated matching algorithms, we've created a solution that addresses the fundamental challenges of traditional PO matching while providing a platform for continuous improvement and innovation.

As businesses face increasing pressure to do more with less, technologies like ours will be essential in transforming financial operations from cost centers to value creators. The question is no longer whether to automate PO matching, but how quickly you can implement a solution that delivers both immediate ROI and long-term strategic value.

Artificio specializes in intelligent document processing solutions for finance and accounting operations. Our platform combines advanced data extraction with business process automation to transform how organizations handle their document-intensive workflows.