Does an LLM judge my agent?
No LLM judges your agent. Ackuity uses small language models for threat-detection signals alongside rules and behavioral baselines, correlated with action context. It does not ask a general-purpose LLM for a free-form safety verdict. The distinction is the role of the models, not their size alone.
What is an AI agent kill switch?
An AI agent kill switch is an independent control that stops a harmful agent action before it executes, and the agent has no influence over the decision. A traditional kill switch stops the whole agent. Ackuity works as a control switch: it acts on each action and keeps Terminate, which shuts the container down, for catastrophic cases.
How do you stop an AI agent from taking a harmful action?
You check each action before it runs, from a control the agent cannot influence. That control sits beside the agent in the execution path, weighs every kind of action against context such as the user, the goal and recent history, and then allows, constrains, pauses or blocks it.
What is the difference between an AI guardrail and an execution control?
An AI guardrail checks what goes into and comes out of a model, while execution control checks what the agent is about to do before it runs. Guardrails live inside the model or the agent harness, so the agent they restrain can sometimes reason around them. Execution control sits outside the agent and decides on the action itself, such as a shell command, a SQL query or a refund.
Does Ackuity require code changes?
No. The sidecar runs in the agent's pod, and an init container reroutes traffic through it. Platforms such as Copilot Studio use API injection, and event pull from OpenTelemetry, Langfuse or LangSmith offers an observe-only start.
Where does my data go?
Your data stays in your own cloud account, because Ackuity runs there. For stricter requirements, Ackuity can also hold the agent's credentials and run the action on its behalf, handling mTLS, so the agent never touches the tokens.
Does Ackuity work with NVIDIA OpenShell?
An integration with NVIDIA OpenShell's supervisor middleware is in development. The supervisor inspects the agent's outbound HTTP, GraphQL and MCP traffic, and the middleware lets Ackuity allow, deny or modify it, which maps to Allow, Block and Constrain. Outside OpenShell, the same decision layer runs as the Ackuity sidecar on any Kubernetes cluster.
AckuityRequest assessment 
