Find your Data and Process Sovereignty Score

Authentication and Access. How consistently does your organization enforce strong MFA and least-privilege access across all users, service accounts, and AI systems?

Encryption Standards. How completely is your data encrypted at rest and in transit across every cloud environment you use?

Incident Resilience. How prepared is your organization to keep operating and protect data during a long-term cloud outage or major security incident?

Monitoring and Auditing. How mature is your program for continuous cloud risk monitoring, control testing, and audit evidence collection?

Third-Party Risk. How rigorously do you assess SaaS applications and AI agents for security and data-handling risk before they are integrated into critical workflows?

Budgetary Adequacy. How well is your cybersecurity and AI-risk budget scaled to meet the current threat landscape, including AI-generated attacks?

Breach Absorption. How confident are you that your organization could absorb the financial impact of a major cloud data breach without material harm?

Shadow IT Visibility. How much visibility do you have into unauthorized cloud apps and AI tools running inside your organization?

Security-Enabled Velocity. How well do your current security policies enable innovation teams to move quickly without compromising posture?

Cost Predictability. How accurately can you forecast your AI and cloud compute spend twelve months out, including egress, inference, and lock-in costs?

Geographic Sovereignty. How well does your current infrastructure guarantee that regulated data stays within required jurisdictions?

Physical Control. How confident are you in your ability to physically inspect, seize, or reclaim your data and infrastructure on demand?

Regulatory Compliance. How confident are you that your current setup meets all regulatory mandates applicable to your industry (GDPR, HIPAA, DORA, CMMC, and equivalents)?

Provider Exit Readiness. How ready is your documented exit strategy to move workloads if your cloud provider changes terms, pricing, or availability?

AI Data Containment. How well have you contained the risk of data leaks and intellectual property loss from generative AI tools used inside your organization?

Model Control. How much of your mission-critical AI can you run on infrastructure you own, without a third-party inference API in the path?

Workflow Portability. If your primary cloud AI provider changed terms tomorrow, how quickly could you cut production workflows over to an alternative?

Determinism and Audit. How reliably can you reproduce the exact inputs, model weights, and decision path for an AI-generated output six months after the fact for a regulator?

Automation Independence. How portable are your CI/CD, orchestration, and MLOps stacks across environments, versus being locked to a single provider?

Human-in-the-Loop Authority. How well can you enforce which AI-driven decisions require human review, consistently across every AI system in your organization?