AI-Powered Duty Drawback Optimization
Penny Chen, CEO of Pax, on building AI-powered tariff refunds
The real wedge is not filing paperwork faster, it is turning drawback from a labor service into an optimization engine. A valid claim is a matching problem across imports, exports, HTS codes, timing rules, and substitution rules, so the winner is the system that can search huge record sets and pick the combination that returns the most cash, not the firm with the biggest analyst team.
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Legacy providers still start with messy invoices, bills of lading, CSVs, and ERP exports, then clean and structure them by hand or in old desktop software. That is why claims often take nine to twelve months and why smaller refunds are often not worth serving.
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The calculation itself is constrained by CBP rules, not guesswork. Claims can depend on same article or substitution logic, HTS classification matches, whether goods were used, and export timing windows, which makes brute force review by human analysts impractical at scale.
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This is why drawback is shifting toward software led operators. Pax says it averages 15% better refunds than leading legacy software, and Flexport now markets duty drawback automation with faster payouts and materially higher returns than traditional tools, showing the category is becoming algorithmic.
Going forward, tariff volatility should push drawback toward platforms that combine document extraction, rules engines, and optimization. As more brokers and importers adopt software first workflows, the market should widen from large enterprises to mid market shippers, and refund quality should become a visible competitive metric rather than a back office black box.