AI Automation

InvoiceIQ: Document Processing Pipeline

Extracts data from PDF invoices with OCR and AI, validates, and pushes to accounting software.

Client

Apex Logistics

Industry

Logistics / Supply Chain

Duration

4 weeks

Biggest result

-90%

manual data entry

Overview

Extracts data from PDF invoices with OCR and AI, validates, and pushes to accounting software.

The Challenge

Apex Logistics received over 12,000 invoices per month as PDF attachments. Their finance team manually entered each one into QuickBooks — a process that took 3 full-time employees and still had a 5–8% error rate. Invoices were often paid late, damaging supplier relationships.

Our Solution

We built InvoiceIQ, a document processing pipeline that automatically extracts invoice data from PDF emails using Tesseract OCR, then uses OpenAI to validate and structure the extracted data. The pipeline checks for duplicate invoices, validates amounts against purchase orders, and pushes clean data directly into QuickBooks. Exceptions are flagged for manual review.

See it in action

See the automation pipeline light up step by step — from trigger to output.

Automation Pipeline

Email Received

OCR Extract

AI Validation

QuickBooks Push

Exception Review

Before vs After

Drag the slider to compare the old process with the new one.

Before

12,000

Manual entries/month

After

1,200

Manual entries/month

Manual entries/month

Before

12,000

→

After

1,200

Error rate

Before

5-8%

→

After

under 5%

FTEs on data entry

Before

3

→

After

0.5

Results

0%

Extraction accuracy

0%

Less manual entry

0

Invoices per month

Improvement visualization

Extraction accuracy95%
Less manual entry-90%
Invoices per month12k

Key Features

  • Automated PDF invoice extraction with OCR and AI validation
  • Duplicate detection and purchase order matching
  • Direct QuickBooks integration with error handling
  • Exception flagging for manual review of edge cases
  • Monthly processing dashboard with accuracy metrics

Tech Stack

PythonTesseractOpenAIQuickBooks API

Project Timeline

1

Discover

4 days

Analyzed invoice volume, formats, error patterns, and QuickBooks workflow.

2

Build

18 days

Built OCR pipeline, AI validation layer, QuickBooks API integration.

3

Launch

3 days

Phased rollout — 1,000 invoices/day, scaled to 12,000 over 2 weeks.

4

Optimize

Ongoing

Retrain OCR on new vendor formats, tune duplicate detection thresholds.

"We had three people doing nothing but data entry. Now the pipeline handles 12,000 invoices a month with 95% accuracy. Our team focuses on exceptions only."
D

David Okonkwo

CFO, Apex Logistics

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