01
Straight-through extraction
Documents move from scan to structured fields without re-keying.
Less processing labour per bill and greater volume capacity.
Automating the Bill of Lading
90,000 bills a day, read in seconds instead of minutes.
FirstVal customer — global shipping data company
Shipping & freight documentation
- 80%
- Fewer documentation errors
- 8x
- Productivity per operator
- 6x
- Cost saving per document
01 — The intro
Where the story starts
A bill of lading is the document that holds a shipment together. It is the receipt that goods were loaded, the contract of carriage, and the title to the goods themselves.
Automating it means pulling the key facts off the page and into the payables system fast enough to clear approvals and payments. Traditionally this has been paper-driven work — slow, manual, and error-prone.
- Daily volume
- 90,000
- Manual effort
- 4,500+ hours
- Quality exposure
- 4%
Bills handled across operating centres before automation.
Daily documentation and verification effort at roughly 20 minutes per bill.
Reported manual documentation error rate before model-assisted validation.
02 — The challenge
Read bills of lading in any format, extract every relevant fact accurately, and do it at a cost and speed that scales.
- —Close to 90,000 bills of lading processed every day across operating centres.
- —Each bill carries multiple line items — roughly a million item-level records to document.
- —4,500+ man hours consumed daily, around 20 minutes per bill, across a regional workforce.
- —A reported error rate of around 4% during manual documentation.
Improve
Throughput and accuracy
Reduce
Cost per document and rework
03 — The solution
A document intelligence pipeline that ingests any layout, extracts named entities, reads context, and validates itself before storage.
- 01Engineered an extraction pipeline that accepts documents across formats after annotation.
- 02Trained ensemble models specifically on bill of lading structures.
- 03Named-entity extraction for names and addresses, PO number, instructions, pickup date, item number and attributes, packaging type, freight class.
- 04Context analysis for free-text notes and handwritten instructions.
- 05Auto-validation and storage on cloud with audit trail.
- 06Model optimisation so scans run on a phone in the yard.
- 07Micro-services architecture for scale, with PII handled at every hop.
Impact
1,000 bills of lading processed in under three minutes.
04 — Value logic
How operating change reaches financial value
02
Context validation
Entities, instructions and line items are checked before storage.
Lower correction cost and fewer payment delays.
03
Mobile inference
Teams capture documents at the point of work.
Shorter cycle time without adding fixed terminals or handoffs.
05 — Feature delight
What people actually felt
01
Any format, no rules
Varied layouts handled by the same models — the customer was freed from maintaining brittle rule-based templates.
02
Mobility with AI
A light but accurate model that runs on mobile, so a scan can happen wherever the paper is.
06 — Ground impact
What moved, and by how much
6x
Cost saving
Cost per person for documentation, processing and validation.
90 days
First pilot
Then 12 locations live in under six months.
80%
Error reduction
Models fine-tuned against the human error baseline.
7 sec
Per bill
Extraction, processing and documentation, down from 20 minutes.
07 — Measurement
How the result stays accountable
Speed
Compare the documented 20-minute manual cycle with the seven-second automated processing time.
Quality
Track exceptions requiring human correction against the reported 4% manual error baseline.
Capacity
Measure bills completed per operator and cost per completed document at each rollout location.
08 — CSAT score
Scored by the customer, A+ to D
A responsive, intuitive document AI solution delivered against a measurable financial outcome.
- A+
- AI model and deployment pipeline
- A+
- Customer service and PII data management
- A
- User experience
- A
- Overall impact
09 — More customer stories
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