What it is
A harness that turns an AI agent into a careful systems administrator. The administrator types requests in plain English; the agent runs them across the server fleet through a gateway that classifies, logs and, where necessary, blocks each command.
It runs against the company's private LLM by default, with a cloud model available for non-sensitive work.
What it does
- Fleet health in one screen: disk, memory, services and container status across every server, asked in one sentence.
- Security checks: vulnerability-assessment scripts and CIS Level 1 audits, reported per server.
- Routine operations: updates, file transfers, container deployment and container updates, with a backup prompt before anything risky.
- Firewall requests raised as tickets in the company's ticketing system, through a browser session the human signs in to.
- A library of skills, one per duty, that loads only when needed so a small local model is not overloaded.
How it works
- The agent proposes a command for a named server.
- The gateway classifies it against an allowlist of known read-only commands. Anything unknown, hidden or substituted is treated as a change.
- Read-only commands run immediately. A change is blocked until the human approves it and it is re-run with an explicit confirm flag.
- Every command and its result are written to a dated audit log; remote output is capped so one verbose command cannot flood the session.
- Credentials never pass through the chat: SSH keys, sudo and API keys live in the operating system's credential store.
Design choices
- Guardrails in the code, not in the prompt: a small model can ignore instructions, so the gateway enforces the rules itself.
- Fail closed: the allowlist decides what is safe; everything else needs a person.
- Fleet-wide queries are read-only by design; a single approval can never touch every server at once.
- Two editions, PowerShell and Python, so the console works even where one of them is restricted.