Trax

The AI-Powered Transportation Spend Management Platform.

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Overview

Trax offers a Transportation Spend Management (TSM) platform that leverages artificial intelligence to provide deep visibility and control over global logistics costs. The platform handles complex, multi-modal freight audit and payment, compliance, and provides data-driven insights to drive operational excellence and cost savings.

✨ Key Features

  • AI-Powered Freight Audit
  • Transportation Spend Management
  • Global Payment Services
  • Rate and Contract Management
  • Logistics Data Analytics
  • Carbon Emissions Tracking (Emissions IQ)

🎯 Key Differentiators

  • AI-native platform designed for transportation spend management
  • Focus on data normalization and analytics to provide actionable insights
  • Global capabilities with support for numerous carriers and regions

Unique Value: Transforms raw logistics data into a strategic advantage by using AI to deliver superior audit accuracy, compliance management, and supply chain intelligence.

🎯 Use Cases (4)

Global transportation spend management Automated freight invoice validation Supply chain cost optimization Carrier contract compliance

✅ Best For

  • Managing complex, multi-modal supply chains for Fortune 500 companies
  • Using AI to analyze invoices and identify savings opportunities

💡 Check With Vendor

Verify these considerations match your specific requirements:

  • Domestic-only shippers with simple logistics networks

🏆 Alternatives

Cass Information Systems CTSI-Global nVision Global Data2Logistics

Unlike legacy systems that may bolt on AI, Trax's AI-native architecture provides more sophisticated analysis and automation capabilities for managing transportation spend.

💻 Platforms

Web API

🔌 Integrations

ERP systems TMS systems API

🛟 Support Options

  • ✓ Email Support
  • ✓ Phone Support
  • ✓ Dedicated Support (Enterprise tier)

🔒 Compliance & Security

✓ SOC 2 ✓ GDPR ✓ ISO 27001 ✓ SSO ✓ SOC 1 Type II ✓ SOC 2 Type II ✓ ISO 27001

💰 Pricing

Contact for pricing
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