Invoice Automation for Lagos Logistics Firm

The Problem

A Lagos logistics firm was processing 800–1,200 supplier invoices per month. Four finance staff spent 60% of their working hours manually keying invoice data into their accounting system. Error rates ran at 11%. Month-end reconciliation took 3 full days.

Discovery & Audit (Week 1–2)

Corespec's AI team audited the existing process: how invoices arrived (email, WhatsApp photos, scanned PDFs), how they were validated, and where errors most frequently occurred. We found that 73% of invoices came from recurring vendors in consistent formats — ideal for automated extraction.

Build & Integration (Week 3–4)

Pipeline designed: document ingestion → OCR pre-processing → GPT-4o vision extraction → validation against vendor master data → API push to accounting system. Confidence scores routed high-certainty invoices to auto-process and low-certainty ones to a human review queue.

Testing & Go-Live (Week 5–6)

300 historical invoices processed to validate accuracy: 96.4% field-level accuracy on first pass. Staff trained on the review queue. System went live on schedule.

Results at 90 Days

• 80% reduction in manual data entry
• Month-end close reduced from 3 days to 4 hours
• Error rate dropped from 11% to 0.9%
• Finance team refocused from data entry to supplier relationship management and cash flow analysis