Risk Overview
Detailed analysis of your AI infrastructure risk factors and recommendations for improvement
Oak Cover Score
Overall risk management score across all models and deployments. Higher is better.
77
AI Risk Score
59
Data Risk
6
Deployment Risk
13
Regulatory Risk
3
Usage Risk
3
Risk Factors
AI Risk Score
Score: 59You have 2 models with high AI risk scores (above 60). Customer Support LLM, Clinical Triage Model are contributing significantly to your overall risk.
Recommendations:
- Review and retrain models with high AI risk scores
- Implement additional safety checks and validation layers
- Consider using more conservative model configurations
Affected Models:
Top Recommendations
Actions you can take to reduce your risk score
Enable stricter output filters
Impact: -6Reduce hallucination risk by enabling high-sensitivity filters on customer-facing prompts.
Refresh training data
Impact: -5Add recent support tickets to reduce drift.
Infrastructure Overview
Summary of your AI systems and deployments
Models
3
2 high AI risk
Deployments
3
2 high-criticality
Active Alerts
2
1 critical