Turn inbound logistics documents into structured operational data with AI-assisted classification, extraction and validation connected to your systems.
Who this is for
Freight forwarders, transport companies, warehouses and back-office teams handling BOL, POD, invoices, customs files and operational forms at volume.
Problems it solves
- 01
High manual volume across document types
- 02
Inconsistent formats from partners and carriers
- 03
Slow exception handling when fields are missing
- 04
Limited traceability from document to system record
What the first version can include
Document intake from email and file sources
Classification and field extraction models
Validation and exception review queues
Structured output to operational systems
Monitoring for accuracy and processing volume
How 4RTY helps
Process mapping
Product design
UX and UI
Technical architecture
Development
Integrations
Launch support
Documentation
Typical integrations
MVP & scale path
MVP
Start small: MVP first
- Ingest documents from email, portals and uploads
- Classify document type and extract key fields
- Validate against shipment, order or invoice rules
- Route exceptions to ops with extracted context
- Write approved data to TMS, WMS or ERP
Scale
Scale later
- Less time opening and re-keying documents
- Faster routing of exceptions to the right team
- More consistent data entering TMS and finance
- Scalable processing as document volume grows
FAQ
Common questions
Which logistics documents can you process?
Common examples include BOL, POD, invoices, customs documents, delivery notes and operational forms, depending on your formats and validation rules.
Do humans still review extracted data?
Yes. We design review paths for low-confidence extractions and exceptions so automation supports logistics teams rather than bypassing them.