Solution Blueprint — AI Automation
Solution Blueprint: AI Document Processing for a Trading Company
Trading & Distribution — GCC
The problem
A mid-size trading company processes 400+ invoices, delivery notes and contracts per week. Two full-time staff re-key documents into the ERP, chase approvals by email, and reconcile mismatches at month-end. Errors slip through; suppliers wait on payment; management sees costs weeks late.
The existing process
Email inboxes as the intake channel, spreadsheets as the tracking system, and an ERP that only receives data after human re-entry. Approvals live in personal inboxes — when someone travels, the process stops.
The solution
An AI document pipeline: documents arrive by email or upload, an extraction layer reads them (OCR + LLM extraction with confidence scoring), validated data posts directly into the ERP through its API, and an approval workflow routes exceptions to the right person on WhatsApp or email. Humans review only low-confidence extractions and exceptions.
Architecture
- 01Intake — shared mailbox + upload portal, every document versioned and logged
- 02Extraction — OCR + LLM with per-field confidence scores and schema validation
- 03Review — only items below the confidence threshold reach a human queue
- 04ERP posting — validated records written through the ERP API with idempotency keys
- 05Approvals — rule-based routing with escalation timers and full audit trail
- 06Analytics — processing time, exception rate and cost-per-document dashboard
Technologies
Projected outcomes
85%
of documents processed without human touch (projected)
4 min
average document turnaround, down from ~1.5 days (projected)
2 → 0.2
full-time equivalents freed for higher-value work (projected)
100%
audit trail coverage on every approval and edit
Solution Blueprint: a technical demonstration of how we solve this class of problem. Figures are engineering projections from comparable deployments, not a specific client’s results.
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