Disruption Scenario Simulator
Trigger simulated disruptions to demonstrate how the AI agent detects, reasons about, and responds to operational risks in real time. Each scenario modifies the simulation state and triggers the agent's observe → reason → decide → act loop.
Warehouse Congestion
Simulates a sudden surge in warehouse load, causing congestion at a major hub. The AI agent should detect the bottleneck and recommend reprioritizing or rerouting affected shipments.
Expected Impact
Increases warehouse load to 95%+, queues spike, congestion score critical
Carrier Failure
Simulates a carrier experiencing systemic failures — high delay probability, low pickup success rate. The AI agent should flag carrier degradation and recommend switching carriers for affected shipments.
Expected Impact
Carrier reliability drops below 0.3, delay probability > 70%
Traffic Spike
Simulates a major traffic disruption on key routes, causing ETA drift for multiple shipments. The AI agent should detect emerging delay risks and suggest rerouting or escalation.
Expected Impact
Traffic level → CRITICAL on major corridors, ETAs shift 2-4 hours
How Scenario Simulation Works
1
Trigger
Operator triggers a disruption scenario
2
Observe
AI agent detects changed operational signals
3
Reason
Agent analyzes root cause and affected shipments
4
Decide
Agent evaluates and scores possible interventions
5
Act
Agent executes or recommends corrective actions