Every AI system needs an operator. It doesn't have to be you, yet.
Production AI is an operational commitment: incidents at inconvenient hours, model updates that need judgment, oversight that regulators expect to be continuous. Standing that capability up internally takes time you may not want to spend before the value is proven.
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We run it for you, with named owners, defined response, and oversight reporting you can forward to your risk committee. And because the goal is your capability rather than our dependency, the handover path is part of the service from day one.
FOR LEADERS WHO
want production AI without building an ops team first.
FOR SYSTEMS THAT
are too important to be someone's side duty.
FOR TEAMS WITH
want to take over gradually, with training wheels on.
01 What you get
01
The operations service.
Named owners for your system, monitoring watched by people accountable for it, and incident response with defined severity and escalation.
02
The update cadence.
Model updates, dependency patches, and improvements shipped on a rhythm you approve, tested before they touch production.
03
The oversight reporting.
A regular operational report in business terms: performance, incidents, decisions, and drift, written for your risk owners.
04
The handover path.
A staged transfer of ownership, role by role, at your pace, with your people running alongside ours until they don't need to.
02 How it runs
Four phases, from our keys to yours.
Dependence is a failure mode. The service is built to make itself smaller.
PHASE 01
Take the keys.
Ownership transferred in: access, runbooks, monitoring, and a severity model agreed with your risk owners.
PHASE 02
Run the routine.
Incidents handled, updates shipped, oversight maintained, with every action logged and visible to you.
PHASE 03
Report and review.
A standing operational review with your team: what happened, what changed, what's trending the wrong way.
PHASE 04
Transfer ownership.
Your people take roles one at a time, shadow first, then lead, until the split of duties is exactly where you want it.
03 Questions we answer
Who answers when the system misbehaves?
How do updates ship without surprises?
What does oversight look like, week to week?
What should our team own, and when?
How do operating costs stay predictable?
What does a clean handover look like?
04 Continue the arc