Primitive
Customs Optimizer
Protect landed cost before shipment design starts.
Customs Optimizer improves classification confidence, admissibility signals, PGA treatment, and Section 232 treatment before the export workflow reaches planning.
Better customs data means cheaper landed cost, stronger admissibility confidence, and fewer broker-facing correction cycles before planning starts.
Optimize first, then carry cleaner customs inputs into planning and execution.
POST /api/customs/optimize POST /api/exports/plan POST /api/exports/execute
Draft primitive direction today. Future contract direction includes batch optimization and asynchronous optimization jobs.
Customs Optimizer Prompt
Paste this into your LLM or run it instantly.
You are helping me run an EntryGo Customs Optimizer review.
Goal:
- clean product customs data before export planning
- improve HS / HTS classification inputs
- identify likely compliance signals
- return machine-readable output for POST /api/customs/optimize
Tasks:
1. Normalize the product description and customs fields.
2. Propose an HS code or candidate classifications.
3. Score confidence and explain the confidence band.
4. Flag compliance issues that require review.
5. Produce output that can feed POST /api/exports/plan.{
"contract_status": "draft",
"optimizer_run_id": "opt_run_demo_1001",
"optimizer_attempt_id": "opt_attempt_demo_1",
"hs_code": "6109.10",
"candidate_classifications": [
{
"hs_code": "6109.10",
"support_score": 0.87,
"rationale_summary": "High confidence apparel match based on product name, description, and materials."
},
{
"hs_code": "6109.90",
"support_score": 0.42,
"rationale_summary": "Alternate apparel classification retained for operator review."
}
],
"confidence_score": 0.87,
"confidence_level": "high",
"recommended_action": "auto_accept",
"confidence_reasoning_summary": "Structured product attributes strongly support a cotton apparel classification.",
"merge_report": {
"normalized_fields": [
"product_name",
"description",
"country_of_origin",
"value"
],
"missing_fields": [],
"overrides_applied": [],
"notes": [
"Draft preview response for the Customs Optimizer contract."
]
},
"retry_available": true,
"attempt_number": 1,
"max_attempts": 3,
"compliance_flags": [],
"metering": {
"billable_event_type": "customs_optimization",
"optimizer_run_count": 1,
"optimizer_attempt_count": 1
}
}Draft preview contract. Production optimizer execution is not yet enabled.
Why it exists
Margin disappears when customs cleanup happens too late.
Teams lose money when weak classification, missing admissibility context, or unclear PGA and Section 232 treatment are discovered after shipments are already being assembled.
Classification quality
Improve classification confidence before planning locks in shipment decisions and landed-cost assumptions.
Admissibility readiness
Surface admissibility, PGA, and Section 232 treatment early so compliance managers review issues before handoff.
Broker efficiency
Reduce broker correction cycles by sending cleaner customs inputs before planning and handoff begin.
Higher-confidence classification lowers expensive landed-cost drift later.
Cleaner admissibility plus PGA / 232 treatment means fewer downstream document and broker exceptions.
Operators can inspect what changed before planning inherits the result.
Optimization makes the rest of the export stack cheaper.
Planning inherits cleaner customs truth. Execution inherits cleaner commercial intent. Compliance teams get a clearer review surface before shipment structure is committed.
That is why Customs Optimizer exists as its own primitive instead of hiding customs cleanup inside spreadsheets or after-the-fact broker correction loops. Start with the quickstart or inspect the contract.