Solution · AI Operations
AI Operations as a service: who runs your AI in production every day, not just on launch day
This isn't automating one more task. It's the whole function: someone watching that your AI systems keep working, fixing what drifts, and responding when something breaks — on an ongoing basis, without you building an internal team for it.
The problem
Your AI worked in the demo. Nobody's watching that it still works next Tuesday.
- You launched an agent or an AI system months ago and nobody's assigned to watch it: if it fails, your customer finds out before you do.
- The team that built it — internal or a one-off vendor — has moved on to something else; the system's still alive but has no operational owner.
- Every incident gets fought as a fire drill: someone drops what they were doing, investigates, patches it, and goes back to their real job.
- There's no function that decides when to iterate, when to escalate a case, and when to retire something that no longer pulls its weight — so nobody decides.
Cost of staying the same
An AI system nobody operates doesn't fail on day one: it fails quietly, weeks later, once nobody quite remembers how it was built. Every ownerless incident becomes a lost afternoon for someone who shouldn't be the one handling it, and every system with no iteration degrades until it stops delivering what it promised. The bill doesn't show up on any error report; it shows up as AI that "just doesn't move the needle like it used to."
The solution
We run your AI Operations as a continuous outsourced function — monitoring, iteration, and on-call — without you building an internal team
- 1We take over your AI systems in production — the ones you already have, the ones you're launching now — with real access and visibility into what they do and how they perform.
- 2We actually monitor: cycle times, failure rates, cases that go off-script. Not a dashboard nobody looks at, but someone who responds when something drifts.
- 3We iterate on data, not gut feel: we identify bottlenecks and failure patterns, and fix the system before the problem reaches your customer.
- 4We escalate what needs human judgment and document every decision, so at any point you can see exactly what's happening — or bring it in-house if you ever build your own team.
What changes
What you stop losing
Your AI stops depending on someone remembering to check on it: it gets someone with an explicit mandate to keep it running, every day.
Mechanism
Failures stop being discovered by your customers: they get caught and fixed at the operations layer, before they reach the other side.
Mechanism
You don't build an AI Operations team to run one system: you hire the function already running, and decide later whether to bring it in-house.
Mechanism
What we measure: incident response time, failure rate caught before it reaches the customer, and coverage of AI systems with an assigned operational owner.
What we measure
Spec sheet
- Work it removes
- not having anyone run your AI systems in production after launch
- Typical setup
- 1–2 weeks for handover; continuous operation from ramp-up
- Input
- your AI systems already in production and the operational access needed
- Output
- the AI Operations function running — monitoring, iteration, and escalation — as a continuous service
- Works with
- Tus sistemas de IA en producción
- Can connect to
- AI Operations salary calculatorImplementa's role framework
- What we measure
- incident response timefailure rate caught before the customercoverage of systems with an operational owneriteration cadence
- Good fit for
- companies with AI systems already in production that need someone to run them without building an internal team from scratch
- Not a fit for
- anyone with no AI system in production yet, looking for a first implementation
Frequently asked questions
Building a team means constructing the function in-house — hiring, training, governing. This is hiring the function already running, without the months-long ramp before an internal team performs. If you want to build your own team later, we help with that too — it's a different decision, not this one.
It's the concrete form outsourcing takes: a continuous service that runs, monitors, and iterates your systems already in motion. "Outsourcing" is the build-vs-buy decision; this is the function already working — the part that comes after you decide.
No. We start from what you already have in production — whether you built it, another vendor did, or we did — and take over running it. If you also need to build something new, that's a separate project that can run alongside this one.
Want it running in your business?
You’ve pinned the problem. We ship the fix and leave it measured.