Case study · Freight forwarding

Document OCR for a Taiwan freight forwarder

Bills of lading, invoices, and packing lists were retyped by hand. We built a system that reads them and fills in the data, leaving people to check only what needs checking.

Freight
Industry
Taiwan
Region
AI
Service

The challenge

Shipping documents arrive in many layouts from many parties. Staff keyed each field into the operations system by hand. Volume grew faster than headcount, and a single mistyped field could hold up a shipment later.

Approach

What we did

01

Collect real documents

Across senders and layouts, including the messy scans.

02

Build field extraction

Focused on the fields operations actually uses.

03

Add confidence checks

Uncertain fields are flagged for review instead of guessed.

04

Write into the existing system

The team keeps its current workflow.

Technical

Architecture

01

OCR and field extraction

Layout-aware reading across document formats.

02

Confidence scoring

Each field scored; low-confidence fields go to a review queue.

03

System integration

Validated data written into the client's operations system.

Related

A system to build,
or one that needs taking over?

Book a consultation →