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Case Study

How iFIT Eliminated Manual Freight Audit Bottlenecks and Saves 3,500+ Hours Annually With AI-Driven Spend Intelligence

 

As iFIT’s freight volumes increased, manual audit and reporting workflows became a constraint on both the logistics and finance teams. While their legacy audit provider performed basic checks, it lacked the data structure and automation required to support the complexity of modern freight, particularly for unplanned accessorial charges and financial attribution.

By partnering with BlueCargo, iFIT introduced an AI-driven freight spend intelligence layer that automates invoice validation, dispute management, and financial reporting, reducing manual effort and improving cost visibility.

 
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iFit Health Fitness High Res Transp
iFit and BlueCargo data
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Industry: Connected Fitness Equipment

Operational Focus: Cost Control, Audit Accuracy, and Financial Visibility

Key Challenge: Manual audit bottlenecks & limited cost visibility

 

The Challenge

Bridging Freight Complexity and Financial Rigor

Before BlueCargo, iFIT relied on a legacy freight audit provider that focused primarily on validating planned charges. Complex accessorials such as detention, demurrage, terminal handling, and variable surcharges were often treated as pass-through costs due to limited validation logic and insufficient data structure.

iFIT needed a solution that could immediately reduce manual effort while supporting deeper cost attribution and scalability as data maturity expanded—without adding headcount or introducing IT complexity.

The whole reason we shifted into BlueCargo was that we weren’t getting the line-item level detail or the data structured in a way we could actually act on. Now, we have customized data we can use to get faster insight and better control over our freight spend.

Jeff Simper, Director of Brokerage & Logistics, iFIT

The SOLUTION

From Manual Audits to Freight Spend Intelligence


iFIT selected BlueCargo to modernize its freight audit approach, shifting from a service-heavy model to a technology-first foundation designed for scale

  • Freight Cost Integrity & Structured Spend Data
  • End-to-End Dispute Automation
  • Trust, Then Scale

Automated data lets me pull what I need and move forward immediately, without the manual rechecking that slows teams down as operations scale.

Ellen Rose, Logistics Manager, iFIT

Freight Cost Integrity & Structured Spend Data

BlueCargo converts unstructured freight invoices (PDFs, carrier statements, terminal documents) into structured, queryable data. This enables iFIT to consistently analyze freight spend at the container and accessorial level, enabling actionable projects & programs within their supply chain.

This structure gives leadership faster insight and greater control over how US-imported freight spend breaks down: by carrier, lane, terminal, or program, supporting margin analysis and targeted cost-control initiatives.

End-to-End Dispute Automation

Validating an error is only part of the challenge. Resolving it is where time is often lost. BlueCargo automates the full dispute lifecycle across 66 distinct charge types, including complex accessorials governed by terminal- and carrier-specific rules.
As a result:

  • 99.4% of invoices are processed autonomously

  • The iFIT team intervenes only on true exceptions requiring judgment

  • Manual dispute creation, tracking, and follow-up are largely eliminated

This automation materially reduces operational workload while improving consistency and recovery discipline.

Trust, Then Scale

Establishing trust in the data was a prerequisite for automation. With data accuracy
established, iFIT is now positioned to expand automation coverage, increase
financial attribution depth, and scale freight intelligence across additional regions
as data becomes available.

The AI ADVANTAGE

From Audit Execution to Strategic Control

By deploying BlueCargo, iFIT built a foundation for freight cost intelligence, enabling faster insights, stronger controls, and scalable operations beyond simple invoice automation. They implemented an AI-driven foundation for freight cost intelligence that supports faster insights, stronger controls, and long-term scalability.

Document Intelligence (Operational Today)

BlueCargo’s AI ingests unstructured freight documents and converts them into structured, queryable data. This allows iFIT to:

  • Analyze spend by charge type, carrier, lane, and terminal

  • Answer targeted spend questions without building manual reports

  • Reduce data preparation effort across logistics and finance teams

Pattern-Based Anomaly Detection

Rather than relying solely on static audit rules, BlueCargo applies pattern recognition across historical freight data to surface charges that deviate from expected norms.

This supports:

  • Earlier identification of irregular charges

  • More consistent dispute initiation

  • Reduced leakage from overlooked accessorials

Strategic Resource Allocation

By automating invoice validation, dispute workflows, and recurring reporting, BlueCargo removes a substantial portion of repetitive manual effort from day-to-day operations. As a result:

  • Time previously spent reconciling invoices is redirected toward carrier strategy and cost control initiatives

  • Teams operate with greater leverage, not increased headcount

  • The organization is positioned to scale freight complexity without scaling administrative burden

WITH BLUECARGO AI

METRIC LEGACY PROVIDER BLUECARGO AI
Invoice Processing Manual validation & reporting 99.4% no-touch processing
Exception Handling Manual dispute creation & follow-up Automated dispute workflows
Audit Scope Planned charges only 66 charge types audited
Time Impact Manual Workflow 3,500+ hours eliminated annually
Financial Impact Reactive Corrections $208K+ invalid charges prevented
Looking Ahead

Built for Scale

iFIT now operates on a freight-cost foundation designed for scale. With BlueCargo serving as the system of record for freight cost integrity, the organization is positioned to extend structured freight intelligence to additional geographies and freight types as data becomes available, without reintroducing manual bottlenecks.

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