Trust isn't a feature; it's a system. Our 9-Pillar Framework provides the complete blueprint for AI that enterprises can confidently deploy.
Security
Protecting AI systems from emerging threats
- Prompt injection defense
- Data exfiltration prevention
- Model weight protection
- Access control and authentication
- Supply chain security
Reliability
Ensuring consistent, predictable performance
- Performance benchmarking
- Load testing and scaling
- Failover and redundancy
- Quality of service guarantees
- Uptime monitoring
Integrity
Maintaining accuracy and preventing misinformation
- Hallucination detection
- Fact verification systems
- Output validation
- Confidence scoring
- Error correction protocols
Privacy
Safeguarding sensitive information
- PII detection and redaction
- Data minimization
- Consent management
- Cross-border compliance
- Right to deletion support
Explainability
Making AI decisions understandable
- Decision trace generation
- Feature importance analysis
- Natural language explanations
- Audit trail creation
- Stakeholder reporting
Ethical Use
Preventing bias and ensuring fairness
- Bias detection and mitigation
- Fairness metrics
- Inclusive design principles
- Harmful content filtering
- Use case restrictions
Model Provenance
Tracking AI lineage and changes
- Version control systems
- Training data documentation
- Model cards and documentation
- Change management
- Rollback capabilities
Vendor Risk
Managing third-party AI dependencies
- API monitoring
- SLA enforcement
- Vendor assessment
- Concentration risk analysis
- Contingency planning
Incident Response
Rapid detection and remediation
- Real-time alerting
- Automated remediation
- Incident classification
- Root cause analysis
- Stakeholder communication