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Wayam AI
ManufacturingProcurementRepresentative scenario

Early Detection of Port Congestion Shocks & Dynamic Ocean Freight Rerouting

A global consumer electronics manufacturer importing component sub-assemblies from Asian supplier hubs into North American and European manufacturing plants.

Run on Purti · Supply Chain Resilience

A congested node with one route already diverging around it

The challenge

    01

    Unexpected port labor strikes and canal blockages caused ocean shipping lead times to double from 21 days to 45 days without warning.

    02

    Supply chain planners relied on delayed freight forwarder email updates, learning of container delays only after ships were queued at anchor.

    03

    Unannounced container delays caused assembly line shutdowns at downstream electronics assembly plants, costing $150,000/day in idle labor.

How Purti solves it

    01

    Global Maritime Signal Monitoring

    Purti ingests satellite AIS vessel tracking, port congestion metrics, labor strike news feeds, and customs throughput data in real time.

    02

    Predictive ETA & Lead-Time Recalculation

    Recalculates container arrival ETAs dynamically, flagging 14 delayed shipments 3 weeks before port arrival.

    03

    Downstream Stockout Exposure Isolation

    Maps delayed container part numbers directly against plant BOM schedules, identifying 4 high-value customer orders at risk.

    04

    Dynamic Freight Rerouting & Mode Switching

    Evaluates alternative transit routes-recommending air-freight buffer shipments for critical components while rerouting remaining containers to secondary ports.

    05

    Automated Logistics Supplier Dispatch

    Dispatches updated booking orders directly to logistics carriers via API.

The outcome

zero assembly line downtime by selectively air-freighting
$0Mzero assembly line downtime by selectively air-freighting
  • 3-week advance lead-time visibility into maritime port congestion shocks.

  • Zero assembly line downtime by selectively air-freighting critical component buffers before stockouts occurred. $2.1M saved in customer SLA delivery penalties and factory idle labor expenses.

Representative scenario: a modelled industry situation showing how this accelerator applies. Figures are projections, not a named client result.

Capabilities used

Every accelerator is assembled from the same capability layer, so a workflow you adopt here shares its foundation with the rest of the portfolio.

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