HTS Classification Accuracy: Reaching Up to 96%

May 20, 2025 10 min read By Dr. Sarah Kim, Head of AI Research

After 18 months of intensive research and development, we're thrilled to announce that our ClearPath Structured 17B-16E MOE model has achieved up to 96% accuracy in HTS code classification—a breakthrough that sets a new industry standard and demonstrates the transformative power of purpose-built AI for trade compliance.

The Challenge of HTS Classification

The Harmonized Tariff Schedule (HTS) contains over 17,000 classification codes, each with specific rules, exceptions, and interpretations. Traditional automated classification systems struggle with:

  • Ambiguous Product Descriptions: Many commercial documents lack the technical detail required for precise classification
  • Complex Rule Hierarchies: Classification often depends on subtle material compositions and intended use cases
  • Regulatory Nuances: Different countries may interpret the same product differently
  • Continuous Updates: Trade regulations evolve constantly, requiring models to adapt quickly

Our Technical Approach

Achieving up to 96% accuracy required a fundamental rethinking of how AI models understand and classify trade goods. Our approach combines several breakthrough innovations:

1. Mixture of Experts (MOE) Architecture

Our model uses a specialized MOE architecture with 16 expert networks, each fine-tuned for specific product categories. This allows the model to develop deep expertise in areas like textiles, electronics, machinery, and chemicals while maintaining overall coherence.

Expert Network Specializations

Textiles & Apparel
Electronics & Components
Machinery & Equipment
Chemicals & Pharmaceuticals
Automotive & Transportation
Food & Beverages
Raw Materials & Metals
Medical & Scientific

2. Structured Decoding with vLLM

Traditional language models often generate invalid or inconsistent outputs. Our implementation of vLLM's structured decoding ensures that every classification output conforms to valid HTS formats and includes required metadata.

Sample Structured Output

// JSON output for a wireless headphone classification
{
"hts_code": "8518.30.2000",
"description": "Headphones and earphones, wireless",
"confidence": 0.97,
"reasoning": "Product contains Bluetooth receiver and is primarily designed for personal audio reproduction",
"alternative_codes": ["8518.30.1000", "8518.30.8000"],
"material_composition": "Plastic housing, metal components",
"duty_rate": "0%"
}

3. Multimodal Document Understanding

Our model combines multiple input modalities to build a comprehensive understanding of each product:

OCR Text Extraction

High-accuracy text extraction from invoices, packing lists, and certificates using our transformer-based encoder-decoder model.

Visual Context Analysis

Integration of document layout, images, and visual elements to understand product specifications and context.

Knowledge Graph Integration

Real-time access to regulatory databases, tariff schedules, and trade agreements to ensure current and accurate classifications.

Benchmark Results

We evaluated our model against a comprehensive dataset of 100,000+ manually classified trade entries from multiple customs brokers. The results speak for themselves:

96.3%
Top-1 Accuracy
Exact HTS code match
99.1%
Top-3 Accuracy
Correct code in top 3 suggestions
1.8s
Average Processing Time
End-to-end classification

Industry Impact

This breakthrough in HTS classification accuracy has immediate implications for global trade:

Cost Savings

Reduced classification errors mean fewer customs delays, penalty assessments, and post-entry corrections.

Time Efficiency

Automated classification reduces manual review time from hours to seconds, accelerating the entire supply chain.

Compliance Assurance

Higher accuracy means better regulatory compliance and reduced risk of audits or penalties.

Real-World Validation

Our breakthrough has been validated in production environments with impressive results:

"The accuracy improvement is remarkable. We've seen a 72% reduction in classification errors and significantly faster clearance times. This technology is transforming how we approach trade compliance."

Trade Compliance Director, Major US Retailer

What's Next

While up to 96% accuracy represents a significant milestone, we're already working on the next generation of improvements:

  • Real-time Regulation Updates: Automatically adapting to changes in trade regulations as they're published
  • Multi-language Support: Expanding to process documents in 15+ languages
  • Federated Learning: Continuous improvement through privacy-preserving collaborative training

Experience Up to 96% Accuracy

See how our breakthrough HTS classification technology can transform your trade compliance operations.

Request Demo