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The control layer between an autonomous agent and the world. A powerful identity for systems that isolate, constrain, authorize, monitor, and govern AI agents before they can act.
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About this name
AI agents are becoming capable of browsing, coding, calling APIs, manipulating files, executing workflows, and taking actions on behalf of users.
The problem is no longer simply whether an agent can act. It is whether the agent can act within a defined operational boundary.
AgentConfinement names the infrastructure that creates that boundary.
Websites, APIs, files, databases, devices, networks, users, and external systems.
An autonomous system capable of reasoning, planning, tool use, and multi-step execution.
Confinement turns vague autonomy into explicit operating rules.
Run agents inside isolated environments with controlled access to compute, files, and systems.
Translate organizational rules into machine-enforced boundaries for autonomous behavior.
Control which tools an agent can call, when it can call them, and what parameters it may use.
Restrict outbound connectivity and create explicit trust boundaries around agent environments.
Require explicit authorization before high-impact or irreversible actions are executed.
Record actions, decisions, tool calls, policy events, and resource usage across agent runs.
AgentConfinement can anchor an entire product family around secure autonomy, controlled execution, and enterprise agent governance.
An isolated execution environment for autonomous agents and their tools.
Security controls designed specifically for agents capable of taking action.
A programmable policy engine for defining agent operating boundaries.
A control point between autonomous agents and external tools, APIs, and services.
Controlled autonomy for organizations deploying agents into sensitive workflows.
A complete operational record of agent actions, permissions, and policy decisions.
“Confinement” communicates a precise idea: an agent can remain capable without being given unrestricted access to everything around it.
Defines where autonomous behavior stops.
Makes permissions explicit and enforceable.
Separates agent execution from sensitive systems.
Creates an operational framework for responsible deployment.
A broad technical territory spanning AI security, infrastructure, governance, and autonomous systems.
Allow agents to write and execute code without exposing unrestricted production access.
Control navigation, credentials, websites, downloads, and external actions.
Deploy autonomous workflows inside organizational permissions and compliance boundaries.
Create explicit controls around transactions, approvals, accounts, and sensitive operations.
Give agents broad reasoning capability while controlling data access and external actions.
Put guardrails around agents capable of modifying cloud resources, systems, or deployments.
The next generation of AI systems will not simply generate information. They will perform actions.
That changes the infrastructure problem. Identity, permissions, isolation, policies, approvals, observability, and runtime boundaries become part of the AI stack itself.
AgentConfinement positions directly at that emerging control layer.
Specific enough to communicate a category. Broad enough to support an entire security platform.
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