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Industries / Logistics & Supply Chain
🚚 Logistics & Supply Chain

Ten Thousand Invoices a Month.
None of Them Should Be Touched by Hand.

Logistics operations run on documents — invoices, bills of lading, proof of delivery, carrier rate sheets, purchase orders. Every one of them manually processed is a cost you can eliminate. We build the pipelines that do it at 99% accuracy, at any volume, integrated into your ERP on day one.

€10–20
Cost per manually processed invoice
(Ardent Partners research; includes labour, errors, rework)
99%
Extraction accuracy from our
logistics document pipeline
~7 wks
Payback period on our
invoice automation project

Where Logistics Operations Haemorrhage Time

These aren't abstract problems. They're the Monday morning reality for most logistics and supply chain teams.

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Invoice Data Entry at Scale

Carrier invoices, supplier invoices, freight bills — each with different layouts, different field names, different currencies. A team of people keying them into an ERP, one by one. At 10,000+ invoices a month, this is a full-time operation that exists only because nobody built the alternative.

12% Error Rate and the Rework Behind It

Manual data entry errors are inevitable at volume. The real cost isn't the error — it's everything downstream: AP disputes, duplicate payments, reconciliation time, vendor relationship friction. A 12% rework rate on 10,000 invoices means 1,200 fixes every month. Every month.

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Routing Delays That Cost Relationships

When a document sits in an inbox waiting to be opened, classified, and forwarded, the clock is ticking. Late payment notifications, missed SLAs with carriers, disputes that escalate because nobody caught the discrepancy for three days.

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No Visibility Until It's a Problem

Paper-based or email-driven document flows have no real-time visibility. You find out something went wrong when a vendor chases you, not when the document landed. Building in tracking and exception alerting isn't an AI project — it's a pipeline architecture question most teams haven't got to yet.

What We Actually Built

This is a real project. The numbers below are from it.

Document Automation · Logistics

From 40 Hours of Data Entry to Zero

Three people manually keying 10,000+ invoices a month into the ERP. 40 hours of work per week, a 12% error rate, and a backlog that grew faster than the team could clear it. Two automation attempts had already failed — both on data cleaning and format variability. The problem wasn't willingness; it was that the previous attempts treated document diversity as a preprocessing problem instead of a model selection problem.

Before Manual entry Spreadsheet Email routing 3 days / 12% errors
After Invoice in AI classify & extract Auto-route to ERP Minutes / 99% accuracy
Annual savings
€155K
Error rate
12% → <1%
Manual processing
85% eliminated

3 FTEs redirected to vendor negotiations (est. €135K loaded salary) + error remediation eliminated (est. €20K/yr). Payback: ~7 weeks.

See full case study library →

What a Production Logistics Pipeline Actually Looks Like

Not a demo. A system that handles your actual document formats — including the ones that don't follow any template.

Multi-format document ingestion

Accepts documents from email attachments, SFTP drops, EDI feeds, API webhooks, and manual portal uploads. All routes converge into one normalised pipeline. You don't need to standardise your inputs.

Layout-agnostic extraction

We use Azure Document Intelligence for form field extraction combined with GPT-4o for variable-layout understanding. The model handles invoice variants from 50+ carriers without retraining for each one.

Business rule validation before ERP write

Every extracted record passes through your validation rules — VAT number checks, PO matching, carrier rate verification, duplicate detection — before anything touches the ERP. Low-confidence extractions go to a human review queue, not into your books.

Native ERP / accounting system integration

Direct API integration with SAP, Oracle NetSuite, Microsoft Dynamics, AFAS, or your existing accounting system. Not a CSV export — a live write with confirmation and error handling.

What We Build On

Azure Document Intelligence
Form extraction & OCR for structured documents
GPT-4o
Variable-layout understanding & classification
Python / FastAPI
Pipeline orchestration & REST API layer
PostgreSQL
Extracted data storage & audit log
Celery + Redis
Async job processing & queue management
ERP API (SAP / NetSuite / Dynamics)
Live write integration with validation

How many invoices does your team process manually?

Tell us the volume and the ERP you're using. We'll tell you honestly what a pipeline would look like and what it would cost.

Get a scoped estimate