The staging environment for AI agents.

What Agent Etna is

A staging environment you point at the agent you already run — support, sales, coding, research, any kind. Agent Etna profiles it from its code, builds an environment around it, and runs it through scenarios that probe how it behaves: the everyday tasks, the security probes, the awkward conversations. An independent judge scores each one, and what fails comes back as a proposed change you open as a pull request, or skip.

Everything runs in an isolated sandbox against a throwaway copy of your agent — never the live one. Every proposed change is validated on held-out scenarios and a safety battery before it can become a pull request, and nothing merges without you.

Who it's for

Builders who have shipped an agent and now need it to behave reliably, faithfully, and predictably as it meets real users. We work with:

• First-time builders shipping their first production agent and looking for a safety net.
• Experienced creators running a mature agent who want to compound small wins instead of triaging incidents.
• Enterprise teams who need every change to be auditable, gated, and reversible.
• Other AI agents calling in programmatically — Agent Etna's own API and MCP server are built for a machine caller, not just a human at a keyboard.

The principles we build by

Safety is the default, not an afterthought.

Every scenario runs in an isolated sandbox. Your live agent, its users, and its data are never touched. The worst case for a failed simulation is exactly nothing.

Honest judgment, with receipts.

Changes are graded by something independent of the agent itself, against the instructions you approved for it. Every verdict quotes the transcript it judged — evidence you can read, not a score you have to take on faith. A change only becomes a pull request if it made the agent better on the scenarios that exposed the gap; it can't slip through by gaming a metric or quietly weakening a safeguard.

Small steps that compound.

One simulation reads like a small win. That's the method. Every merged change becomes a floor your agent can never fall below again — a ratchet, enforced by regression replay — and the next simulation goes after whatever is now weakest.

Your models, your keys.

Agent Etna runs on your own LLM key, on every plan. You pick the models and pay providers directly, at cost — we never mark up a token. The subscription funds the platform, so our incentive is your agent getting better, never your token bill getting bigger.

You always have the off-switch.

Nothing merges without you. Every change arrives as a pull request you review, and the record of what we did stays in your repository even if you stop using us. You can disconnect at any time.