Application maintenance services for the AI systems we build — a named escalation point after we leave.
On a check-in call, days after we handed over their AI tool, a multi-company middle-market contractor asked the question every buyer eventually asks: “Is there an escalation point if we need some work on it — can we put in some sort of maintenance structure?” Yes. That is what this is: we stay on for monitoring, model changes, and patching — monthly, cancelable, no lock-in.
Official services partner of the platforms defining AI
NVIDIA
Anthropic
The build has a plan. The maintenance structure usually doesn’t.
From a check-in call with a multi-company middle-market contractor: their purpose-built AI tool was deployed and paid for, with rollout pending to around 30 users — and the one open question was who owns it from here.
“Who owns this after you leave?”
The demo lands, the keys are in your pocket, and then the real question surfaces. If the answer is “call us if something breaks,” you don’t have support — you have a phone number. The buyer’s own words: is there an escalation point, someone who is actually supporting the actual tool.
The model underneath your tool changes
Model vendors retire versions on a published schedule. The version your AI system was tuned on has an end date — and if nobody is watching the calendar, you find out when output drifts or a deprecated endpoint stops answering, not before.
The scanner never stops
Vulnerability findings keep arriving after go-live — new CVEs in the libraries your tool depends on, new findings on the AI stack itself. Who patches, who remediates, how fast: if that isn’t agreed before launch, it becomes an argument after it.
The rollout is real now
The tool was in a few hands; now thirty people depend on it Monday morning. The first confused user, the first odd answer, the first export that looks wrong — somebody has to own that queue, or the rollout stalls and the tool quietly dies.
Nobody wants the 24/7 contract
Classic application support is priced and staffed for a whole estate of legacy software — multi-year terms, a ticket queue, a team that has never seen your system. That is the opposite of what a delivered AI tool needs.
Handover that isn’t real
If the only documentation lives in the builder’s head, you didn’t take delivery — you took custody. Real maintenance starts with docs and training your team can actually run with, so staying with us is a choice, not a dependency.
Without a maintenance structure, the tool decays quietly.
What it looks like when a delivered AI system has no named owner. Your numbers will differ — the maintenance agreement we write first puts figures on yours before you commit.
From an anonymized engagement — a multi-company middle-market contractor; one purpose-built AI tool, delivered with one iteration outstanding
A maintenance structure you can describe in one sentence.
The same team that built the system stays on to run it — with a named escalation point and an agreement written before the first invoice. Three steps, fixed order.
- 01
Write the maintenance agreement
Before anything starts: what we monitor and where it alerts, response times by severity, how patches and model upgrades are scheduled, what the monthly cost covers, and the named escalation point when something matters. Plain terms, monthly billing, cancelable.
- 02
Monitor, patch, fix the drift
The steady state: health and cost monitoring on the system, security patches as findings land, and model-drift work when a vendor retires or changes a model — regression-tested against your real cases before anything goes live, so an “upgrade” never surprises the thirty people using it.
- 03
Make the handover real
Documentation your team can follow, admin and user training, and a runbook for the common cases. The point is that you could take it over — which is exactly why the arrangement is cancelable. Staying is a choice you make every month.
Software maintenance services, rebuilt for systems with AI inside.
Search for software maintenance services and you get the classic AMS pitch: a ticket queue, a team rotating through your estate, a multi-year contract. That model was built for legacy software that changes slowly. A purpose-built AI system doesn’t — the model underneath it has a published retirement schedule, the libraries patch continuously, and the people using it notice output drift before any dashboard does.
So the shape is different. The people who built your system are the people who answer when you escalate. The scope is one system, not your whole estate. And because the documentation and training make it yours, the monthly arrangement is cancelable — support you choose, not a dependency someone engineered.
Is there like an escalation point — can we pay for supporting the actual tool? We need to put in some sort of maintenance structure.
Led by Peter Enestrom.
Application support and maintenance services, answered straight.
What buyers ask after the build is done — in their words, not ours.
The ongoing work of keeping a delivered system healthy after the builder hands it over: monitoring, security patching, fixes when something breaks, and updates when the platform underneath changes. Classic application maintenance covers legacy software estates. Ours covers the AI systems we build — where the model underneath changes on a schedule and the people who built it are the right people to fix it.
You do — that’s the whole point of the handover. You get the documentation, the admin and user training, and a runbook for the common cases. If you want us to stay on as the named escalation point, that’s a monthly arrangement you choose and can cancel. The handover is real either way; maintenance is a service, not a leash.
That’s scheduled work, not an emergency — model providers publish retirement and deprecation dates well in advance. We track the versions your system depends on, test the replacement against your real cases, and ship the change before the old version disappears. The failure mode without maintenance is discovering the drift when a user notices the answers changed.
Scope, people, and terms. Classic AMS is a ticket queue across your whole software estate, staffed by whoever is on shift, on a multi-year contract. This is application support services for one purpose-built system: the people who built it take the escalations, the scope is the system and its AI models, and the arrangement is monthly and cancelable.
Three things: health (is the system up and answering), cost (what the model usage is running, so the bill never surprises you), and security (vulnerability findings on the stack, with patches applied on an agreed schedule). Where it makes sense, monitoring lands in your own dashboards so your team sees what we see.
A flat monthly figure agreed up front — no question-mark price tag, no percentage-of-estate pricing. It’s cancelable: the documentation and training we deliver make the system genuinely yours, so staying with us is a decision you make every month, not a dependency we engineered.
Then that’s what you get. Every build we deliver comes with documentation, training, and a walkthrough with whoever will own it internally — the “keys in your pocket” version. The maintenance structure exists because buyers ask for it, not because the tool needs us to keep running.
Start with one workflow.
Tell us where your team loses hours. We will come back with a straight answer on whether AI can help, what it would take, and what it would pay.