Trade compliance has historically been a highly manual, error-prone function. Operators spend countless hours reconciling customs data, matching tariffs to product codes, and managing exceptions when shipments don’t align neatly with documentation.

With tools like Parabola, teams can automatically ingest data from customs forms, normalize formats, validate HS codes, and even push reconciled data into ERP systems. Instead of chasing paperwork, compliance teams gain time back to focus on strategic sourcing, vendor negotiation, and risk management.

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For a full breakdown on how automation is reshaping trade compliance, read our blog here.

Tariffs rarely stay still. One policy decision can change duty rates overnight, and operators need a way to understand the downstream financial impact fast. Scenario modeling provides that capability.

With Parabola, teams can build flexible models that ingest SKU-level purchase order data, apply different tariff rates or policy scenarios, and output cost impact analyses in minutes. This allows finance and sourcing leaders to answer questions like: What happens if a 10% tariff becomes 25%? What if quotas tighten next quarter? Instead of relying on best guesses, leaders get data-driven visibility to inform sourcing, pricing, and margin protection strategies.

How to automate tariff scenario modeling in Parabola:

• Pull in data: Connect to ERP or order management systems (e.g., NetSuite, Shopify, or CSV uploads) to load SKU-level purchase order data.
• Transform data:
  • Clean and normalize SKUs, units, and supplier codes.
  • Add custom columns for tariff rate scenarios (e.g., 10%, 15%, 25%).
• Apply AI-driven transforms: Use natural language prompts to calculate cost impact under each tariff scenario.
• Output results: Push data into Google Sheets, BI dashboards, or Slack alerts for finance and sourcing teams.

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Use our tariff scenario modeling template and start automating!

Every international shipment generates a stack of customs paperwork — invoices, packing lists, certificates of origin. Traditionally, teams re-key this data manually into spreadsheets or ERP systems, a slow process rife with opportunities for error.

Parabola’s customs digitization workflows use AI to extract, structure, and validate customs data at scale. That means operators can automatically capture key fields from PDFs or scanned documents, standardize values like SKUs or dates, and push clean data into downstream systems. The result is faster clearance, fewer disputes, and real-time visibility into cross-border flows.

How to automate customs document digitization in Parabola:

• Ingest documents: Forward emails with attached PDFs or Excel customs files directly into Parabola.
• Extract structured data with AI:
  • Use “Extract from email” or “Extract from file” steps to identify tables and header fields.
  • Apply AI instructions to capture key data points (e.g., PO number, HS code, origin, SKU).
• Validate & standardize:
  • Normalize dates, SKUs, and HS codes.
  • Apply business logic rules (e.g., “All HS codes must be six digits”).
• Send downstream: Push validated records into NetSuite, TMS platforms, or a shared Google Sheet for real-time access.

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Automatically parse and standardize any customs document for free.

The final step in tariff readiness is understanding the full landed cost of goods. Beyond the base purchase price, companies need to account for duties, freight, insurance, and customs fees to know whether an item is profitable to source and sell.

With Parabola, landed cost workflows can automatically aggregate these inputs from multiple systems, apply business logic to calculate per-unit landed costs, and surface discrepancies. Teams can break down landed costs by SKU, supplier, or region, enabling smarter decisions about sourcing, pricing, and margin optimization. In a volatile tariff environment, this level of cost transparency is non-negotiable.

How to automate landed cost calculation in Parabola:

• Pull in data: Import purchase order data, carrier invoices, and customs fee reports.
• Join data sources: Combine records at the SKU/PO level with “Combine tables” steps.
• Apply calculations:
  • Use AI-powered custom transforms to calculate duties, freight, and insurance allocations per unit.
  • Standardize cost categories across suppliers.
• Flag discrepancies: Add logic to highlight mismatches between invoices and expected landed costs.
• Share results: Push per-unit landed costs into ERP, reporting dashboards, or auto-send summaries to finance teams.

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Automate your landed cost calculation by consolidating freight invoices, supplier costs, and duty fees into a SKU-level breakdown using Parabola.