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AI Security · Data Sovereignty · Private LLM

Secure private AI deployments

Private AI is a control problem: where do prompts, documents, and tool outputs live?

Patterns that work

  • Gateway / proxy in front of every model call (logging, DLP, allowlists)
  • Prompt-injection guards on ingress for untrusted text
  • Local or VPC-hosted weights for the sensitive slice; cloud frontier for the rest
  • Red-team loops before agents get production tools

Practical split

Use local / VPC models for private corpora. Use the current frontier board (/leaderboard) for hard reasoning when contracts allow. Don’t confuse a security brochure with a measured breach-cost reduction — instrument first.