About Enforgate
A security boundary for AI agents.
AI agents are starting to take real actions — sending emails, querying databases, moving money, deleting files. The problem isn't whether they canact, it's whether they should, and whether anyone can see what they did. Enforgate sits between your agents and the tools they call (over the Model Context Protocol) and turns every action into a decision: allow, deny, or require human approval — all recorded in an audit log.
Why we built it
Traditional security assumes a human is behind every action. Agents break that assumption: they act fast, at scale, and unpredictably. Giving an agent raw credentials to your tools is like handing an intern root access and hoping for the best. We think agentic systems need the same thing every other part of your stack has — a policy enforcement point, least-privilege access, human escalation for high-risk actions, and a complete audit trail. Enforgate is that control plane.
What we believe
Secure by default
No policy means deny. A malformed rule fails closed. An audit write failure stops the call. Safety is the default path, never an opt-in.
Everything is auditable
Every tool call gets a verdict and an immutable record. We hash arguments — never store them raw — so you get accountability without hoarding sensitive data.
Humans in the loop
Risky actions can pause for a person to approve or deny — with full attribution — instead of silently going through or being blanket-blocked.
Least privilege
Agents get exactly the tools and parameters a policy allows, scoped per key and per organization. Nothing more.
Want to talk?
Questions about Enforgate, security, or whether it fits your stack? We'd love to hear from you.