Use cases

Where AI agents do real work

We look for high-volume workflows with judgment, exceptions, and handoffs. If the work can be mapped, governed, and measured, agents can run it. These are the six categories where we deploy most often.

How we pick the first workflow

The wedge is one painful workflow, not a whole-company program. We look for four signals. Volume high enough that small time savings compound. Rules that a person could write down if asked. Exceptions that follow patterns rather than pure improvisation. And a clear owner who will tell us when the output is wrong.

Work that fails those tests is work we say no to. We turn down projects when we cannot name the workflow that will measurably improve. That is not modesty. Agents deployed into work nobody can define are how AI-first efforts stall.

Every deployment below follows the same shape: mapped workflow, exception playbook, agent team, company brain, scored output, and an operation we run. The domain changes. The method does not.

What a deployment costs

A single agent pilot is $15,000 to build and $2,500 per month to operate. A full agent system for a department is $35,000 to build and $6,500 per month to operate. Enterprise deployments are quoted. Full detail is on the pricing page.

Everything starts with the two-week AI-First Scan. The scan stands alone, with no obligation to continue.

Bring us one painful workflow. We'll make it AI-first.

Two-week AI-First Scan. A ranked opportunity map. A deployed system your team does not have to babysit.

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