World's Largest Consumer Electronics and Technology Company Saves $3M Annually in Freight Costs with AI agents

Manual freight costing consumed 2K+ hours monthly across teams 

The company's freight operations relied on a legacy freight tool – systems designed for simpler supply chains that couldn't handle electronics manufacturing complexity. Teams spent entire days manually calculating costs for shipments moving through multiple countries, carriers, and transportation modes. 

Freight costing became a bottleneck that delayed business decisions. When components shipped from semiconductor fabs in Taiwan to assembly facilities in Asia, then to distribution centers across North America and Europe, their legacy systems required manual intervention at each transfer point. Teams tracked costs through spreadsheets because the tool couldn't identify shipments with more than three legs – a critical limitation when electronics components routinely traveled through six or seven transfer points before reaching customers. 

The currency complexity alone overwhelmed their processes. Beyond the basic USD, Euro, RMB, and INR transactions, the company dealt with Yen for Japanese component suppliers, Won for South Korean semiconductor partners, Singapore Dollar for Southeast Asian assembly operations, Great Britain Pounds for European distribution, Canadian Dollar for Canadian operations, and Mexican Peso for North American manufacturing facilities. Each currency required separate rate calculations, exchange rate applications, and accessorial charge computations that consumed specialized resources. 

Contract management paralyzed carrier relationships. Every rate change from their 150+ carriers triggered manual updates across multiple systems. When ocean freight rates fluctuated weekly during peak seasons, teams worked overtime just maintaining current pricing. The process took three weeks minimum, meaning their systems reflected outdated rates while actual shipments moved at current market prices, creating constant cost discrepancies. 

Our people were drowning in spreadsheets instead of managing supplier relationships. We had brilliant logistics professionals spending 80% of their time on data entry because our systems couldn't handle the complexity of modern electronics supply chains.

— Director of Global Transportation

Invoice auditing created the most expensive blind spot. Their selective audit process covered roughly 33% of freight invoices, meaning two-thirds of their $2 billion annual freight spend went unvalidated. The audit team could only process invoices that matched specific criteria – single-leg shipments, standard currencies, and basic accessorial charges. Complex electronics shipments involving multiple carriers, currency conversions, and specialized handling requirements simply couldn't be audited with existing capabilities. 

This limitation enabled four critical error types to persist undetected: carrier invoice calculations mismatching actual shipment parameters, unusual accessorial charges going unquestioned, missing invoice data elements preventing proper validation, and shipment-contract misalignments creating systematic overbilling. These errors compounded across thousands of weekly shipments, creating millions in annual revenue leakage that remained invisible until year-end reconciliations revealed the damage. 

The data fragmentation made problems worse. Shipment details lived in the legacy tool while carrier contracts resided in separate systems, invoice data arrived through various EDI formats, and cost allocations required manual spreadsheet consolidation. Teams couldn't correlate information quickly enough to identify discrepancies before payments processed, turning error detection into expensive recovery efforts rather than prevention.

How Pi delivered $3M in annual freight savings

Intelligent freight rate calculation across multi-carrier networks 

Pi, pando's AI agent for logistics playing the role of an AI freight audit & pay specialist, processes complex rate calculations that previously required manual intervention from specialized teams. The agents analyze shipment parameters – weight, dimensions, origin, destination, service requirements – against carrier rate matrices to calculate precise costs within seconds. Pi handles multi-leg complexity seamlessly, tracking cost accumulation as shipments transfer between ocean carriers, air freight providers, and ground transportation networks throughout electronics supply chains. 

Real-time contract rate management across global carriers 

Pi dons the role of an AI freight procurement analyst to maintain current rate information across all carrier relationships, processing contract updates as they occur rather than through manual batch cycles. When ocean freight rates change during volatile periods, Pi immediately applies new pricing to pending shipments while maintaining historical rates for cost reconciliation. The agents handle complex rate structures including tiered pricing, volume discounts, and seasonal adjustments without human intervention. 

Pi eliminated our three-week contract update cycles entirely. When carrier rates change, our systems reflect new pricing immediately. Our carrier partners now prefer working with us because we can respond to market conditions in real-time.

— Senior manager, Carrier relations

Comprehensive freight invoice validation and error detection 

Pi's audit capabilities examine every freight invoice against shipment records and contract terms, identifying discrepancies that manual processes missed. The agents detect calculation errors in complex multi-currency transactions, flag unusual accessorial charges requiring investigation, and identify missing documentation before payment processing. Pi validates invoice line items against actual shipment parameters, catching overbilling attempts that selective auditing couldn't address. 

Advanced multi-leg shipment cost tracking 

Pi follows electronics shipments through complex routing scenarios, maintaining cost visibility as components move from semiconductor fabs through assembly facilities to distribution centers. The system tracks costs across carrier handoffs, currency conversions, and transportation mode changes, providing complete cost accounting for components that travel through seven or eight transfer points before reaching customers. 

Finally having complete cost visibility across our supply network changed everything. We can now make informed decisions about component sourcing and manufacturing locations based on true landed costs rather than estimates.

— Vice president, Supply chain operations 

Predictive freight billing anomaly detection and resolution 

Pi's machine learning identifies billing patterns that indicate potential errors before they impact payments. The agents analyze historical data to establish normal cost ranges for specific shipping lanes, flagging invoices that exceed expected parameters for investigation. Pi predicts which carrier-route combinations typically generate billing disputes, enabling proactive communication to prevent issues. 

Accelerated freight payment processing and dispute resolution 

Pi expedites payment cycles by pre-validating invoice accuracy and flagging only genuine discrepancies for human review. The system processes routine freight bills automatically while routing complex disputes to appropriate specialists with complete documentation packages. Pi's validation reduces payment delays that previously strained carrier relationships and increased financing costs. 

Dynamic freight cost allocation across operations 

Pi provides precise cost allocation for complex electronics shipments involving multiple business units, product lines, and geographic regions. The agents calculate accurate cost distributions when single shipments contain components for different product families, ensuring proper financial accounting across manufacturing operations while supporting transfer pricing requirements for international operations.

Pi fundamentally changed how the company approaches freight management, shifting from reactive cost tracking to predictive intelligence. The $3 million in annual savings represents just the beginning – Pi's continuous learning ensures the system becomes more sophisticated as it processes additional data. Teams now focus on strategic carrier relationships and supply chain optimization rather than administrative tasks. 

The transformation established a foundation for autonomous freight operations where intelligent agents handle routine decisions while human expertise drives strategic initiatives. Most importantly, the company gained competitive advantage through superior cost visibility and operational efficiency, positioning them for continued leadership in the dynamic electronics market.