Use Cases · Domain 04
Supply chain, logistics & industrial automation
Complex, multi-variable physical operations — where the invariants are the laws of physics, capacity, and law itself.
Three lenses on the same proof engine
AI-generated code
PLC programming for roboticsAudit AI-generated Structured Text for assembly lines and prove the machine state-space contains no configuration where arms physically collide.
Warehouse IoT scriptsVerify AI-written edge code for autonomous forklifts and sorting systems before it runs on the floor.
Model outcomes
Predictive-maintenance invariantsProve AI failure-prediction models stay inside the thermal and mechanical degradation bounds the physics allows.
Inventory optimizationVerify a supply-chain optimizer never produces a logic trap — such as ordering stock that exceeds physical warehouse volume.
Agent behavior
Autonomous procurement agentsMonitor B2B agents authorized to negotiate and sign supply contracts, blocking any agent that exceeds corporate spending limits.
Fleet-routing agentsAudit delivery-routing agents to prove every route complies with maximum legal driver-on-duty hours and freight-weight bounds.
Bring your domain's hardest rule
If you can state the rule that must hold, an authorized TrueVectors evaluation can check the AI's work against it — deterministically, with a receipt. Tell us the invariant that keeps you up at night.
TrueVectors verifies code, outcomes, and agent behavior. Trust through proof.