AIKINSEY is designed for regulated, sovereign, and mission-critical environments where every AI action needs a clear control path.
Customer data never co-mingles. Deployment boundaries, tenant isolation, encryption keys, and access rules remain under enterprise control.
Every AI action ties to authenticated identity, role, policy, source system, data scope, and approved purpose.
Immutable records capture who asked, what model ran, which data was used, what action happened, and whether a human approved it.
Configurable approval gates route high-stakes actions to humans while routine decisions flow under policy and monitoring.
Controls map to HIPAA, SOC 2, ISO 27001, EU AI Act, FedRAMP, GDPR, PCI DSS, and sector-specific obligations.
Model version, provider, cost, latency, risk, evaluation score, and compliance status are tracked across the lifecycle.
Security and governance materials for procurement, risk, compliance, and executive review.
SOC 2 aligned controls, ISO 27001 program, HIPAA compliance program, FedRAMP readiness, and EU AI Act conformity roadmap.
Encryption at rest and in transit, key management, vulnerability management, incident response, logging, backup, and disaster recovery.
DPA, subprocessors, data residency options, customer-managed keys, retention policies, and deletion workflows.
Pre-completed CAIQ-Lite, SIG Lite, AI governance questionnaire, and procurement documentation for enterprise risk teams.
| Phase | Status | Scope | Target |
|---|---|---|---|
| Security foundation | Complete | Encryption, IAM, audit logging, vulnerability management, incident response. | Live |
| SOC 2 control alignment | In progress | Security, availability, confidentiality, processing integrity, privacy controls. | 2026 |
| Industry compliance programs | In progress | HIPAA, FedRAMP readiness, EU AI Act mapping, GDPR data rights. | 2026–2027 |
| Advanced assurance | Planned | Third-party penetration testing, model risk documentation, AI impact assessments. | 2027 |
These principles are operational controls, not marketing claims.
AI augments human decision-making. High-risk actions escalate to accountable humans, and override decisions are recorded.
Every AI decision should be explainable to the enterprise and to the people affected by it, with model, data, and policy context captured.
Data stays within the deployment boundary. Residency, encryption, retention, and model access follow enterprise-defined policy.
Bias testing, sensitive-use review, risk scoring, and deployment refusal rights are built into governed AI workflows.
Models drift, regulations change, and operating patterns evolve. Governance includes real-time quality monitoring and periodic reassessment.
Read our Trust Framework, review compliance documentation, or speak with our security team.
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