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Challenge

Cross-Border Trade & Customs Clearance Orchestrator with CrewAI

Cross-border maritime trade documents between Singapore and regional ports require multi-party validation across customs, phytosanitary, and bill-of-lading forms. Build a collaborative multi-agent workforce using CrewAI to automate customs review. Reduce manual review processing time and achieve reliable exception routing.

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Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Build a collaborative multi-agent trade clearance automation workforce using CrewAI.

Delivery guide

How work is evaluated

Evaluation

Evaluates document anomaly detection rate and multi-agent coordination correctness.

Datasets

Shared data for this challenge

Review public datasets and any private uploads tied to your build.

Evaluation rubric

How submissions are scored

These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.

Dimensions
2 scoring checks
Binary
2 pass or fail dimensions
Ordinal
0 scaled dimensions
Dimension 1

hs_code_match_check

Ensures HS code evaluation aligns with declared tariff tables.

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Dimension 2

crew_task_completion_rate

Ratio of tasks successfully resolved without unhandled exceptions. • target: 1 • range: 0-1

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

What you should walk away with

  • Define CrewAI agents with dedicated roles: Customs Specialist, Fraud Examiner, Logistics Coordinator

  • Establish sequential and hierarchical task execution crews for multi-document parsing

  • Automate cross-matching between Bills of Lading, HS Code declarations, and packing slips

  • Implement human handoff triggers when customs discrepancies exceed severity bounds

Resources and assets

Reference links and supporting material

Dataset notes

Synthetic cross-border shipping document manifest dataset including declared goods, invoice values, and HS codes.

How this agent runs

Evaluates document anomaly detection rate and multi-agent coordination correctness.

Challenge input

JSON customs packet containing declarations and bill of lading

CrewAI

Assigned framework for multi-agent delegation.

Evaluated output

JSON clearance status and agent logs

Checks for
  • Ensures HS code evaluation aligns with declared tariff tables.
  • Ratio of tasks successfully resolved without unhandled exceptions. • target: 1 • range: 0-1
Proof of success
  • Benchmark: TradeClear-MultiAgent-Bench
  • Crew Task Completion Rate target: 100%
  • 1 public reference case
Runtime evidence
  • Python execution harness
  • Python sandbox (unavailable on Versalist)
View technical recipe

Configured tools

Action Space
  • CrewAI · Required
  • crewAI · Optional
  • Decipher AI · Optional

Evaluation contract

  • hs_code_match_check · Weight 1
  • crew_task_completion_rate · Weight 1

Recipe state

This is a preview. The configuration can change before the evaluation recipe is locked.

Frequently Asked Questions about Cross-Border Trade & Customs Clearance Orchestrator with CrewAI