Iron Trust is earned.
Even by agents.
You would not hire a new employee and give them the keys to the kingdom on day one. AI agents should earn autonomy the same way: through maturity, access discipline, consistent behavior, and provable compliance.
A trust score is not a label. It is a living profile.
Iron Gorilla continuously scores each agent from the evidence it leaves behind: what it can access, what it actually uses, how often it complies, who changed it, and whether its runtime behavior still matches its baseline.
What goes into the score?
Over 50 variables feed the proprietary scoring model. We expose the categories and representative signals your teams need to reason about autonomy, while keeping exact weights and secret-sauce variables intentionally undisclosed.
- Static posture1
- Policy compliance2
- Behavioral detection3
- Upstream MCP risk4
- Human stewardship5
Trust changes what happens before the agent acts.
The score is not a vanity metric. It is an enforcement input. Iron Gorilla uses trust to decide when an agent can move quickly, when it needs heavier inspection, and when a human must approve the next step.
High-trust agents earn speed
Known agents with clean histories and stable behavior can clear routine actions with fewer checkpoints, while hard policy remains enforced.
Medium-trust agents stay supervised
Standard inline evaluation continues across policy, data handling, connector use, and audit capture until the agent earns more autonomy.
Low-trust agents get contained
New agents, risky integrations, unusual disk or network activity, and behavioral drift can trigger reduced permissions, deeper scanning, or human approval.
Static controls tell you what was configured. Trust tells you what has been earned.
Roles and permissions describe what an agent may attempt. Trust Profiles measure whether it has earned the autonomy to attempt more.
Policy answers whether an action is allowed. Trust adds context about whether this agent, at this moment, should receive fast approval or deeper scrutiny.
Audit explains what happened after the fact. Trust Profiles change enforcement before the action executes.
Regulated organizations can let agents do more when trust is visible.
Banks can let proven agents handle more routine investigations. Healthcare teams can separate normal care coordination from risky PHI movement. Insurers can accelerate clean claims without relaxing controls. Government and defense teams can demand attribution before autonomy expands.
See how trust profiles change agent autonomy in real time.
Bring the agent you want to deploy. We will show how trust, policy, behavior, and audit combine before it acts.