AI GRC FOR SUPPLY CHAIN & LOGISTICS
Build Resilient Supply Chains.
Mitigate Model Risk. Ensure Operational Integrity.
TestSavant.ai is the GRC platform for mission-critical logistics AI. Validate demand forecasting models, secure IoT data, and deliver audit-grade evidence for trade and operational compliance.
85%
Reduction in Forecast Model Risk
Continuously validate models to prevent costly stockout or overstock situations.
95%
Increase in Disruption Detection
Identify anomalous data from IoT sensors and partner feeds before they cause delays.
90%
Decrease in Compliance Breaches
Automate evidence generation for trade, security (ISO 28000), and operational audits.
Solution Bundles for Supply Chain
Deploy pre-configured GRC packages for the most critical AI applications in logistics and manufacturing.
Demand Forecasting Integrity
- Continuous validation and drift detection for forecasting models
- Bias checks to ensure fairness across regions and products
- Immutable audit trail of all model changes and performance metrics
IoT & Sensor Data Security
- Real-time anomaly detection for data from IoT devices and sensors
- Guardrails to prevent spoofed or corrupted data from influencing decisions
- Evidence of data integrity for operational and security audits
Logistics & Route Optimization Safety
- Approval workflows for AI-driven changes to critical routes or schedules
- Guardrails to prevent agentic AI from making unsafe or non-compliant decisions
- Red teaming to discover vulnerabilities in routing and optimization logic
Supplier Risk & Compliance Automation
- Automated monitoring of supplier data for potential risks and disruptions
- Guardrails to ensure AI-driven procurement aligns with compliance mandates
- One-click reporting for trade, security, and partnership compliance
From Threat Model to Enforced Control
How our platform translates specific supply chain AI risks into automated, auditable defenses.
| Threat / Failure Mode | Guardrail Decision (UGM + Nero) | Test Methodology (Coliseum) | Result |
|---|---|---|---|
| Inaccurate Demand Forecast | Continuous monitoring, challenger models, and automated alerts for model drift. | Adversarial data injection to test model robustness against unexpected market signals. | More resilient forecasting; lower stockout/overstock risk. |
| Spoofed IoT Sensor Data | Real-time anomaly detection, data integrity checks, and validation of data sources. | Simulate malicious or corrupted sensor data streams to test detection capabilities. | Higher trust in operational data; fewer bad decisions. |
| Unsafe Agentic Action | Approval gates for critical actions (e.g., rerouting shipments); tool-use sandboxing. | Adversarial prompts designed to force unsafe or non-compliant logistics decisions. | Prevention of costly operational and compliance errors. |
Frequently Asked Questions
How do you validate the accuracy of AI-driven demand forecasts?
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Our platform continuously runs challenger models alongside your production forecast AI. We use our red-teaming engine to inject adversarial data (like simulated market shocks) and monitor for drift. When performance deviates, we flag it for review or trigger a controlled retraining cycle, providing a full audit trail for model risk management.
Can your platform secure data from thousands of IoT sensors?
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Yes. Our runtime engine is designed for high-throughput data streams. It applies real-time anomaly detection to identify and quarantine spoofed or corrupted sensor data before it contaminates your planning systems. Our policies enforce data integrity rules, ensuring you can trust the data powering your operational AI.
How do you prevent an agentic AI from making a costly logistics decision?
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We enforce human-in-the-loop controls through policy-as-code. Any high-risk action proposed by an AI agent—like rerouting a critical shipment—is automatically gated. The decision is routed to a designated human approver via a workflow, with the entire sequence (request, context, approval, timestamp) logged for audit.
Does this help with trade and security compliance like ISO 28000?
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Absolutely. Our platform helps you provide evidence of a secure supply chain. We generate immutable logs of data access, model behavior, and security tests. These artifacts can be used to demonstrate robust digital security controls, which is a key component of modern frameworks like ISO 28000 and CTPAT.
Can we deploy this in our private cloud to protect sensitive route data?
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Yes. We offer flexible deployment models, including private VPC and on-premise options. This ensures your most sensitive logistics data, supplier contracts, and proprietary model logic remain within your security perimeter. We also integrate with customer-managed keys (KMS/HSM).
Upgrade Your AI Governance from a Supply Chain Risk to a Resilience Driver
Schedule a confidential briefing to see how TestSavant.ai provides the control needed to build a more intelligent, secure, and resilient supply chain.
