For regulated teams in finance, healthcare, and government, the public cloud is often not an option for sensitive AI workloads. You need a private AI infrastructure that provides the same scale and flexibility as the cloud while maintaining absolute control over your data and secrets.
The Private AI Reference Architecture
1. Network Isolation and Air-Gapping
Use Kubernetes NetworkPolicies and Service Mesh (Istio) to enforce zero-trust networking. For the highest security requirements, we design fully air-gapped clusters that have no direct access to the public internet.
2. Encryption at Rest and in Transit
Ensure that all patient or financial data is encrypted using keys that you control. This includes your vector databases and feature store.
3. Forensic-Grade Audit Logging
Implement structured audit logs that track every model decision and data access event. This is the foundation of your SOC 2 and regulatory readiness.
Final Takeaway
Private AI infrastructure is about data sovereignty. By building your AI platform on a private, isolated Kubernetes foundation, you ensure that you can leverage the power of LLMs without compromising your organization's security or compliance standing.
Need help designing or building private AI infrastructure on Kubernetes? We help regulated teams build secure, isolated, and compliant AI platforms. Book a free infrastructure audit and we’ll review your private AI strategy.
