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Operate

Make intelligent systems reliable.

Getting an agent to work once is easy. Trusting it to work every day inside a business is the hard part. We put the controls, monitoring, evaluation and permissions around automated systems so they can be used without someone watching every run.

Sound familiar?

You are probably here because of one of these.

If more than two apply, the problem is usually further upstream than it looks, and the first conversation is about finding where.

  • An agent works in a demo and you will not let it touch a customer
  • Your vendors switched on AI agents inside tools you already pay for
  • Nobody can list what your agents can reach or what they can change
  • A run reports success and you cannot confirm anything changed
  • Spend moves with usage and the invoice is the first time you see it

What you get

What arrives.

  • An inventory of every agent and integration, what it can reach, and what it can change
  • Blast radius ranked, with approval gates on the actions that warrant one
  • An evaluation set and thresholds, so a change to the model is a measurable event
  • Confirmation from the system that was supposed to change, rather than a run that reports success

Who this is for

Teams putting automated systems in front of customers, money or regulated data. Anyone whose vendors shipped agent features they did not ask for.

When to look elsewhere

A research sandbox where autonomous tool use is the point. These controls exist for systems with consequences.

Tell us what's happening.

Thirty minutes is enough to work out whether this needs a small fix, a focused project, or nothing from us at all.

A person reads every inquiry, usually replying within two business days.