Make enterprise AI adoption safe.
CAGIS.ai is the enterprise control plane for AI agents. We believe teams shouldn't have to choose between moving fast with AI and staying in control — so we built the guardrails that let them do both. Guardrails for AI agents.
Agents got a terminal. Governance didn't keep up.
In the space of a year, AI stopped suggesting code and started running it — reading files, executing shell commands, hitting the network, and calling tools at machine speed on every laptop. The productivity is real. But the controls enterprises rely on for people — approvals, audit, least privilege, DLP — were never wired up for an agent that acts thousands of times a day.
That gap is where secrets leak into prompts, a prompt-injection turns into an exfiltration, and spend runs without attribution. CAGIS closes it — at the boundary where the agent actually acts.
Five disciplines, one name
The name is the mandate. Cost, Agent, Governance, Intelligence, Security — the five things an enterprise has to get right to adopt AI with confidence, brought together in one control plane.
Token and spend metering, budgets, and adoption analytics — so AI value is measured, not assumed.
Governance that reaches every agent — Claude Code, Codex, and hosted surfaces — under one policy.
A native allow / ask / deny policy, every decision audited and attributed to a user and session.
Detection that understands intent — chains, obfuscation, and behavior, not just keywords.
A 60-rule behavioral catalog enforced on-device, offline, and fail-closed by default.
Cages that contain, not cages that confine
Our name carries a second meaning. A good cage isn't a prison — it's the containment that makes powerful things safe to keep close. We design for exactly that: control without unnecessary restriction. The overwhelming majority of what an agent does is useful, and it should stay fast.
So CAGIS doesn't slow the work down — it draws a boundary around the small set of actions that could actually cause harm, and holds the line there. Read a secret, wipe a disk, phone home, move laterally: those meet a decision. Everything else just runs.
- Fast by defaultThe safe majority of agent actions never sees friction.
- Sharp at the edgeOnly genuinely risky actions meet a policy decision.
- Tighten, never loosenOnline checks can only add protection to your local policy.
- Always attributedEvery decision is audited to a user and a session.
The convictions we build on
Four commitments that shape every design decision — from where a check runs to how we choose to price.
On-device by default
Decisions are made on the endpoint, against your policy — so protection holds even offline. Online, CAGIS is defense-in-depth that can only tighten the org policy, never loosen it.
Privacy-preserving
A detected secret is swapped for a reversible vault token before it can reach the model, your logs, or the wire. Only {detector, count} metadata ever leaves the machine.
Fail closed
A crashed gate is never an open door. When the boundary can't be sure, it refuses — so an evasion or an outage can't quietly become an approval.
Outcome-aligned
We measure ourselves on leaks prevented, incidents caught, and spend saved — the value delivered — not seats sold. Price should track the risk removed.
A world where AI is trusted because it's governed
We want AI adoption to be a decision leaders make with confidence, not anxiety — because the controls are already in place, working quietly on every endpoint.
Built to reach every agent you run
From the terminal to hosted surfaces — governed by one policy, one audit trail, one console, and deployed in a single command.