[ AI AGENT GOVERNANCE ]
Govern what your agents do — not just what they say.
AI agent governance is the discipline of controlling what AI agents can do when they act on real systems. SentnelOps is the runtime layer of that discipline: an identity for every agent, policy enforced on every tool call before it executes, and evidence of every decision.
[ WHY GOVERNANCE, WHY RUNTIME ]
Agents are production actors now — merging pull requests, running queries, provisioning infrastructure — and the controls most teams have were built for humans and deterministic services. Guardrails shape what a model says; dashboards record what an agent did. Neither decides what an agent may do. That decision — made per action, at the moment of execution — is AI agent runtime governance, and it is the layer where prompt injection, plan errors, and privilege creep actually get stopped.
The full argument, including the threat model and a working policy, is in What is AI Agent Runtime Governance?
[ THE THREE PILLARS ]
[ THE GOVERNANCE LOOP ]
intercept → decide → enforce → evidence
The SentnelOps proxy receives every MCP tool call before the server sees it, evaluates it against version-controlled YAML policy, enforces the outcome — permit, block, or a Slack approval gate — and writes the full decision record to your own database. It deploys in your VPC with under 15ms p99 overhead; call parameters, responses, and logs never leave your network. That single loop, applied to every action of every agent, is governance in practice.
Start governing your agents this week
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