Customer case study · Document comparison

Asia Shipping reduces document comparison time by 97%+.

See how Asia Shipping uses a Shipflow AI Operator to automate MBL and HBL document comparison and reduce time spent on the task by 97%+.

Measured outcome

97%+

Less time spent on document comparison

Customer
Asia Shipping
Deployed workflow
Document comparison

This result applies to the deployed MBL/HBL comparison task. Results depend on workflow scope, document quality and deployment configuration.

Customer overview

About Asia Shipping.

Asia Shipping uses Shipflow AI Operators to automate a repetitive, document-driven shipment workflow: comparing data fields between Master Bills of Lading (MBLs) and House Bills of Lading (HBLs).

The workflow performs the defined comparison automatically and surfaces the information that requires attention, giving the operations team more time for higher-value work.

MBL
Master Bill of Lading
HBL
House Bill of Lading
3–4 times
Previously compared per shipment

The operational challenge

A necessary document check repeated several times per shipment.

Before Shipflow, Asia Shipping operators manually compared data fields between the MBL and HBL three to four times for each shipment.

The repeated checks were time-consuming, yet the team still needed a reliable way to identify differences and keep the shipment workflow moving.

The deployed workflow

One controlled comparison workflow from document intake to review.

The Shipflow AI Operator connects the repetitive steps into a workflow configured around the document relationship and fields Asia Shipping needs to check.

  1. Identify the document set

    Match the relevant Master Bill of Lading and House Bill of Lading to the shipment and comparison task.

  2. Extract the agreed fields

    Read and structure the shipment data included in the configured comparison scope.

  3. Compare under defined rules

    Apply the field relationships and document rules established for the workflow rather than treating every difference as an error.

  4. Complete or surface the exception

    Finish the routine comparison automatically and send discrepancies or unclear information to the team for review.

The result

97%+ less time spent on MBL/HBL comparison.

Asia Shipping reduced the time spent on the deployed document-comparison task by 97%+.

The automation removes a repetitive operational burden while preserving a clear route for discrepancies and cases that require human judgment.

Human control

Document rules define what passes and what needs attention.

The workflow is configured around the documents, fields and comparison logic required by the operation.

  • The MBL/HBL relationship and fields to compare are explicitly defined.
  • Expected differences can be separated from discrepancies that require action.
  • Unclear, missing or out-of-policy information is surfaced to the team.
  • The measured result remains tied to the deployed document-comparison task.
Explore security and human control

Customer perspective

In Asia Shipping's words.

The Shipflow AI Operator Platform has significantly reduced our manual operational workload by automating high-volume, document-driven shipment workflows. The platform reliably handles repetitive tasks, enabling our operations team to focus on higher-value work while improving both response times and accuracy.

Prior to Shipflow, our operators had to manually compare data fields between MBL and HBL three to four times per shipment, which was extremely time-consuming. With Shipflow, this process is now fully automated by AI.

The Shipflow team has been highly responsive and demonstrates a deep understanding of day-to-day logistics operations.

Jack Yeung
Jack Yeung IT Manager at Asia Shipping

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