Last week, I started testing tools to see if AI could automate data extraction from freight documents—commercial invoices, packing lists, BOLs.
The goal? Less manual data entry, faster processing, fewer errors.
I tested two AI tools: V7Go and Airtable (Others shortlisted were Rossum and Docsumo).
The test to see if AI could extract key info like VAT numbers, HS codes, values etc without manual effort and ultimately use that data for further automations.
Findings: What Worked vs. What Didn’t
✅ Fast & easy upload – AI processed docs in seconds
✅ Basic fields (invoice numbers, dates, totals) were mostly accurate
✅ Clear potential for automation – structured data opens up workflow automation
❌ Not all docs contained the required info – client invoices vary massively
❌ Occasionally pulled the wrong data – e.g., exporter’s VAT instead of importer’s
❌ Still needs human oversight – AI is good, but not 100% reliable
❌ Setup takes effort – the real work is in improving document quality, planning & prompts
Final Thoughts: Is AI Worth It?
- AI definitely has potential to improve freight operations given the right set up.
- The biggest lesson? AI is only as good as the data you give it.
- Next step: Evaluate options for how the final structured data could be best used.
I wrote a more detailed breakdown covering how I tested AI for freight paperwork, what worked, and what didn’t.
I’ll drop the link in the comments if you’re interested.
Anyone else tested AI for freight paperwork?
What’s worked for you—and what hasn’t?
