Agents Makers

Operations team

AI roles for Operations teams.

Operations is where the cost of the second-best process compounds. A delayed handoff between two systems, a manual reconciliation that runs once a week, a checklist that lives in someone's head — none of them are dramatic on their own. Together they are the reason mid-market teams hire 3-5 ops coordinators between Series A and Series C.

An AI Operations role does the cross-system glue work that keeps the operating model running: triage, routing, status updates, exception handling, escalation. It is not a replacement for an Ops leader. It is the layer that lets the Ops leader stop being the routing table.

The operating model in Operations.

  • Cross-system glue, not new system of record

    The role reads and writes to your existing stack (ticketing, CRM, project tool, doc store). It does not introduce a new place where state lives. Your sources of truth stay where they are.

  • Built around your runbook, not a generic template

    Every Ops deployment starts by reading your existing runbook (documented or extracted in scoping) and mapping the role's actions to it. If the runbook is fragmented, scoping tightens it as a side-effect of the deployment.

  • Exception handling is the actual job

    The happy path is easy. The job is the exception path: what the role does when a field is missing, when a system is down, when the rule is ambiguous. Exception policies are authored explicitly and reviewed weekly during ramp.

  • Reports to your Ops dashboard, not a vendor portal

    Throughput, exception rate, cycle time — every metric the role moves is read on the dashboard your Ops team already uses. If you don't have one yet, the deployment includes setting one up.

How it rolls out

The playbook a real Operating Partner runs.

  1. Phase 1

    Map the runbook, name the unit of work

    Document the steps a human takes today. Define the unit of work the role will own (a request, a record, a handoff). Identify the systems involved.

  2. Phase 2

    Author the action policy + exception policy

    What does the role do on the happy path. What does it do when something is missing. Who gets the escalation. This is signed in scoping.

  3. Phase 3

    Wire the connectors, dry-run on historic data

    Integrations come online. The role replays the last 30-60 days of work to validate it would have done the right thing. Discrepancies are reviewed before go-live.

  4. Phase 4

    Live with weekly exception review

    Role goes live. Weekly review of every exception it raised. Refine the policy. By week 4, exception rate should be down meaningfully and cycle time visibly compressed.

  5. Phase 5

    90-day review, expand to the adjacent process

    Read the contracted KPI. If hit, scope the next process — usually one your Ops leader has been wanting to clean up for two quarters. If not, remediation under the operational guarantee.

Ops automation pays back when the role is scoped to a unit of work, not a tool. Every role below is structured that way: a clear unit, a clear policy, a clear escalation, and a baseline read off your existing dashboard.

90-day operational guarantee. We agree on the outcome KPI before launch. If we haven't hit it by day 90, we keep working free until we do.

How it works →

Pick a role. Start deployment.

Every role in this view is hireable, governed, and anchored to the fully-loaded cost of the equivalent hire.