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AI·Finance

Invoice Processing Pipeline

AP team manually keyed 500+ invoices weekly, with frequent errors and delayed payments.

Overview

We built an intelligent document processing pipeline that classifies incoming invoices, extracts key fields, performs three-way matching with purchase orders, and routes exceptions for human review — replacing 30+ hours of weekly manual data entry.

Client

A mid-size manufacturing company...

Timeline

10 weeks

Team

2 engineers

Industry

Finance

The Challenge

A manufacturing company received invoices in dozens of different formats from hundreds of vendors. The AP team spent significant hours every week manually entering invoice data into their ERP, leading to frequent errors, occasional duplicate payments, and strained vendor relationships due to delayed processing.

Our Approach

1

Built intelligent document classification to handle diverse invoice formats from different vendors

2

Trained extraction models for vendor name, invoice number, line items, amounts, and payment terms

3

Created three-way matching automation that cross-references invoices with purchase orders and receiving data

4

Implemented exception handling workflows that route discrepancies to the right reviewer with context

Key Results

96%

Extraction Accuracy

10x

Processing Capacity

30+ hrs

Weekly Time Saved

10 wks

Delivered In

Invoice processing capacity increased substantially without adding headcount

Extraction accuracy reached 96% for key fields

AP team reallocated from data entry to vendor relationship management and exception handling

Early payment discounts captured more consistently

Our AP team was drowning. Five people doing nothing but data entry all day. Now two of them handle the same volume plus exceptions, and the other three moved to work that actually matters. The accuracy is better too.

CFO, Manufacturing Company

Tech Stack

PythonGoGoogle Cloud Document AIPostgreSQLReact

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