Ensure AI Data Sovereignty

Use Case

Control where prompts, gateway traffic, telemetry, findings, enforcement, and audit evidence are processed and retained. Select localized regional cloud services, self-hosted components, hybrid data planes, or fully air-gapped deployment according to geographic, regulatory, privacy, connectivity, and security requirements.

Challenges

Global AI programs must meet different sovereignty requirements without fragmenting security and governance. SaaS-only deployment may be inappropriate when:

• Processing must remain within a specific geographic region
• Sensitive traffic requires inspection inside customer infrastructure
• Data planes and gateways must remain under local control
• Highly secure environments cannot permit external connectivity

Solution

PointGuard AI provides a comprehensive solution for placing AI security services and sensitive processing where sovereignty requirements demand:

1. Select approved regions. Run localized services within regional AWS or Azure environments to keep processing inside required geographic boundaries.

2. Self-host required services. Deploy selected capabilities or the complete platform within customer-controlled infrastructure and existing security baselines.

3. Localize sensitive components. Use a hybrid model that self-hosts the data plane, MCP Security Gateway, and other data-sensitive processing while retaining approved centralized management.

4. Operate fully air-gapped. Run platform capabilities without external network dependencies and route telemetry through internal security and audit workflows.

Organizations retain consistent AI security and governance while controlling sensitive processing, evidence, and data location.

Risks Addressed

Applicable framework risks and controls include:

OWASP Top 10 for LLMs

• LLM02:2026 Sensitive Information Disclosure

OWASP Top 10 for Agentic Applications

• ASI03: Identity and Privilege Abuse
• ASI07: Insecure Inter-Agent Communication

NIST AI Risk Management Framework

• GOVERN 1.4: Transparent risk policies, procedures, and controls are established
• GOVERN 6.1: Policies and procedures address third-party AI risks
• MAP 1.1: Intended use, context, users, and lifecycle risks are documented
• MEASURE 2.7: AI system security and resilience are evaluated and documented