Iron Know which AI agents
have earned your trust.
Not every AI agent should be trusted with the same work. Iron Gorilla gives each one a live trust score based on how it actually behaves — so proven agents move fast, and any agent that starts acting out of character gets a human in the loop before it does damage.
A trust score isn’t a label you assign. It’s earned, and it keeps changing.
Iron Gorilla scores each agent from the evidence it leaves behind: what it can access, what it actually uses, how often it follows the rules, who changed it, and whether it is still behaving the way it normally does.
What goes into the score?
More than 50 signals feed the score. We show you the categories and the kind of evidence behind each one — enough to understand why an agent is trusted — while keeping the exact formula proprietary.
- Static posture1
- Policy compliance2
- Behavioral detection3
- Upstream MCP risk4
- Human stewardship5
Watch a trust score change in real time.
This is the real product, running on sample data. Follow one agent as it earns trust, drifts, and gets pulled in for human review — the moment its behavior changes.
Trust changes what happens before the agent acts.
The score isn’t just a number to look at. Iron Gorilla uses it to decide, in the moment, when an agent can move quickly, when it needs a closer look, and when a person has to approve the next step.
High-trust agents earn speed
Known agents with clean histories and steady behavior can clear routine actions with fewer checkpoints, while your core rules stay fully enforced.
Medium-trust agents stay supervised
Every action keeps getting checked — against your rules, how data is handled, and which tools are used — until the agent earns more independence.
Low-trust agents get contained
New agents, risky connections, unusual activity, or behavior that drifts from the norm can trigger reduced access, a deeper look, or a required human approval.
Most controls only tell you what was set up. Trust tells you what’s actually been earned.
Access rules say what an agent is allowed to attempt. A trust score adds the missing piece: whether it has behaved well enough to deserve less oversight.
A policy decides whether a single action is allowed. Trust decides how much scrutiny the whole moment deserves — and can route an agent to human review on its own.
An audit log explains what went wrong after the fact. A trust score acts in the moment, tightening control before a drifting agent does something costly.
Regulated organizations can let agents do more when trust is visible.
Banks can let proven agents handle more routine investigations. Healthcare teams can separate everyday care coordination from risky movement of patient data. Insurers can speed up clean claims without loosening controls. Government and defense teams can require proof of who did what before an agent earns more freedom.
See how trust profiles change agent autonomy in real time.
Bring the agent you want to deploy. We’ll show how trust, your rules, behavior, and a full audit trail come together before it acts.