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Logistics & Supply ChainOCR AutomationSystem Integration & Automation

AI-Powered Document Processing for Apex Logistics

Automating 5,000+ invoices per month with 97% accuracy

Client: Apex Logistics Group

2025-09-01

12 weeks

OCR & document automation

97%%

First-pass Accuracy

12 seconds

Processing Time per Invoice

5 days

Payment Cycle Reduction

We built an intelligent OCR and document processing system for Apex Logistics that automatically extracts data from 5,000+ invoices per month with 97% accuracy, saving 3 full-time equivalents.

What they faced

The Challenge

Apex Logistics Group processes over 5,000 supplier invoices every month. Each invoice had to be manually reviewed, data extracted, validated against purchase orders, and entered into their accounting system.

The problems:

3 full-time staff dedicated to invoice processing
Average processing time of 8 minutes per invoice — over 650 hours per month
5-7% error rate in manual data entry
Payment delays due to processing bottlenecks
No scalability — growing volume meant hiring more staff

How we solved it

Our Solution

We built an end-to-end document processing pipeline combining OCR, AI classification, and automated validation.

System Architecture

Document Intake — Automated email monitoring and folder scanning for new invoices
AI Classification — Automatic identification of document type and supplier
OCR Extraction — Intelligent text extraction handling varied layouts across 200+ suppliers
Data Validation — Cross-referencing with PO database, flagging exceptions
ERP Integration — Validated data pushed directly to their Sage accounting system
Exception Dashboard — Human review interface for flagged items

AI Components

Custom-trained document classification model
Layout-adaptive OCR with handwriting support
Named entity recognition for supplier, amounts, dates
Fuzzy matching for PO reconciliation

How we delivered

Implementation

Phase 1 (Weeks 1-3): Analysis & Design

Analyzed 500 sample invoices across 50 suppliers
Mapped validation rules and exception criteria
Designed processing pipeline architecture

Phase 2 (Weeks 4-8): Core Development

Built OCR pipeline with AI-powered extraction
Trained classification and extraction models
Developed validation engine

Phase 3 (Weeks 9-11): Integration & Testing

Sage accounting system integration
End-to-end testing with live invoices
Accuracy benchmarking: 97% on first pass

Phase 4 (Week 12): Launch

Production deployment with monitoring
Staff training on exception handling
2-week parallel run with manual verification

Our Tech Stack

Technologies Used

Python

OpenAI

Docker

n8n

"We needed a CRM that actually matched how our sales team works, not another generic tool we'd fight against. Vivado built us exactly that — adoption was immediate and our sales cycle shortened by a third within three months."

What We Delivered

Services & Solutions

OCR Automation

Turn paper and PDFs into structured, actionable data

System Integration & Automation

Connect your tools and automate workflows across systems

Document Processing Automation

Turn paper and PDFs into structured, actionable data — automatically

Internal Workflow Automation

Eliminate manual processes and let your team focus on high-value work

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View All Work

Logistics & Supply ChainOCR AutomationSystem Integration & Automation

AI-Powered Document Processing for Apex Logistics

Automating 5,000+ invoices per month with 97% accuracy

Client: Apex Logistics Group

2025-09-01

12 weeks

OCR & document automation

97%%

First-pass Accuracy

12 seconds

Processing Time per Invoice

5 days

Payment Cycle Reduction

We built an intelligent OCR and document processing system for Apex Logistics that automatically extracts data from 5,000+ invoices per month with 97% accuracy, saving 3 full-time equivalents.

What they faced

The Challenge

The problems:

3 full-time staff dedicated to invoice processing
Average processing time of 8 minutes per invoice — over 650 hours per month
5-7% error rate in manual data entry
Payment delays due to processing bottlenecks
No scalability — growing volume meant hiring more staff

How we solved it

Our Solution

We built an end-to-end document processing pipeline combining OCR, AI classification, and automated validation.

System Architecture

Document Intake — Automated email monitoring and folder scanning for new invoices
AI Classification — Automatic identification of document type and supplier
OCR Extraction — Intelligent text extraction handling varied layouts across 200+ suppliers
Data Validation — Cross-referencing with PO database, flagging exceptions
ERP Integration — Validated data pushed directly to their Sage accounting system
Exception Dashboard — Human review interface for flagged items

AI Components

Custom-trained document classification model
Layout-adaptive OCR with handwriting support
Named entity recognition for supplier, amounts, dates
Fuzzy matching for PO reconciliation

How we delivered

Implementation

Phase 1 (Weeks 1-3): Analysis & Design

Analyzed 500 sample invoices across 50 suppliers
Mapped validation rules and exception criteria
Designed processing pipeline architecture

Phase 2 (Weeks 4-8): Core Development

Built OCR pipeline with AI-powered extraction
Trained classification and extraction models
Developed validation engine

Phase 3 (Weeks 9-11): Integration & Testing

Sage accounting system integration
End-to-end testing with live invoices
Accuracy benchmarking: 97% on first pass

Phase 4 (Week 12): Launch

Production deployment with monitoring
Staff training on exception handling
2-week parallel run with manual verification

Our Tech Stack

Technologies Used

Python

OpenAI

Docker

n8n

"We needed a CRM that actually matched how our sales team works, not another generic tool we'd fight against. Vivado built us exactly that — adoption was immediate and our sales cycle shortened by a third within three months."

What We Delivered