Zero-Trust AI Agent
Architecture where every agent has its own identity, every tool call is authorized, and every output is logged.
What is Zero-Trust AI Agent?
Zero-trust applied to AI agents means no agent, model output, or retrieved passage is trusted by default. Identity is per-agent, tool access is least-privilege, retrieved text is treated as data rather than instructions, and execution traces are exportable for replay. This is the baseline for regulated and sovereign deployments. See AI Agent Security & Data Sovereignty.
Why it matters for on-premise & regulated AI
Zero trust assumes breach — and with agents, “breach” includes a poisoned document convincing an agent to misuse its tools. Per-agent identity, least-privilege tool scopes, and treating retrieved text as untrusted data are enforceable only where you control the runtime. On-premise deployment closes the loop: the enforcement point, the logs proving enforcement, and the data being protected all live in one boundary you own.
Related terms
Putting Zero-Trust AI Agent to work?
VDF AI runs governed AI agents on your own infrastructure — on-premises, sovereign cloud, or air-gapped. Book a working session to map the architecture.
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