Agent Guardrails
Define what AI agents can and cannot do across your environment. Set policies on the people, tools, identities, and resources in the agent chain, and enforce them
The Control Gap
Agents inherit the permissions of the Non-Human Identities they use. No one scopes those permissions to what the agent actually needs
Today, most organizations cannot answer:
Can this agent
access production infrastructure?
Can it push directly
to protected
branches?
Can it use any MCP server a developer installs, regardless of where it came from?
Can it read .env files, SSH keys, or stored credentials on the endpoint?
In most environments, the answer to all of these is yes. Not by design, but by default.
Guardrails at Every Layer
Behind every agent is a chain: the person who deployed it, the agent itself, the tools it uses, the Non-Human Identities it authenticates with, and the resources it reaches.
Clutch maps this chain and lets you set policies at every point on it.
Person
Control who can deploy
and operate agents
Agent
Decide which agents can
operate in your environment
Tools
Set boundaries on what
agents can execute
Identities
Control which identities agents
can authenticate with
Resources
Restrict what systems and data
agents can reach
What You Get
Sensitive Actions
Controlled
Guardrails target specific actions, identities, and resources. An agent that stays within its boundaries runs without interruption.
Context-Aware
Enforcement
The same tool call can be allowed in development and blocked in production. Enforcement accounts for context, not just the action.
Full Forensic
Record
Every policy trigger and every enforcement decision is recorded with complete lineage context.