01
Extraction tuned to freight reality
Vision-model extraction handled the crumpled photos and low-res scans legacy OCR choked on, with field-level confidence scoring on every value — shipment numbers, weights, charges, signatures.
Mid-size freight forwarder · Back-Office Automation
A freight forwarder processed thousands of BOLs, PODs, and carrier invoices a month — every one keyed by hand from a different format. We built an extraction pipeline that reads them all, matches them to shipments, and posts them to the TMS automatically.
/ 01 — The problem
Documents arrived as email PDFs, driver phone photos, and the occasional fax — in hundreds of carrier-specific layouts. Ops staff spent entire afternoons re-keying, and typos surfaced weeks later as billing disputes.
Invoicing waited on POD paperwork being manually matched to shipments, stretching DSO four days past delivery on average.
/ 02 — The build
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Vision-model extraction handled the crumpled photos and low-res scans legacy OCR choked on, with field-level confidence scoring on every value — shipment numbers, weights, charges, signatures.
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Extracted documents were matched to open shipments in the TMS, validated against expected values, and posted automatically. Mismatches queued for review with the exact discrepancy highlighted — a 30-second decision instead of a 12-minute hunt.
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Low-confidence extractions never post silently. The system's honesty about what it can't read is why the operations team came to trust what it does.
/ 03 — The results
“We assumed we'd need an EDI mandate our carriers would never accept. Instead the system just reads whatever they send — including the driver photos.”
/ Free AI audit
Every engagement here started with the free audit. Sennova Labs maps your workflows, prices the waste, and shows you what to automate first.
No obligation · Roadmap is yours to keep