The problem
The launch went fine. Then the system kept running on data nobody tested, through a model update nobody noticed, with nobody reading what it did. Six weeks later someone finds the errors in a reconciliation and asks who was supposed to be looking.
What goes wrong
- Nobody owns it. The vendor that built it moved on, the IT team never agreed to run it, and the first person to notice a failure is a customer.
- It is never re-tested. The model changes, a vendor renames a field, a policy changes, and the system quietly starts getting a different answer.
- There is no trail. When finance asks what the agent did last Tuesday and who approved it, there is no record to show them.
The approach
- Our dedicated support and maintenance team runs the system with an escalation path that ends at a named person.
- Four jobs run after launch: a nightly check that posts to your Slack, evals (tests on your own real cases) re-run after every change, model updates tested before they ship, and a spend cap on each workspace.
- Anything that moves money, contacts a customer, or changes production waits for a named approver, and every action and every deploy is logged where you can read it.
- You hold the accounts, the credentials, and the runbooks.
When it works
It works when the system runs on your real data, a named person reads the morning check, and a human approves every action that costs money or trust. It does not work when nobody on your side owns the backlog or reads the queue.
What changes after launch
Before launch, the question is whether the system works. After launch, the question is whether it still works: on today's data, after the model update, after the payment processor renamed a field. Nobody asks the second question unless it is someone's job.
That is production. A system that touched real money or a real customer this morning, and a named person who finds out first when it did the wrong thing.
Who is on call
Our dedicated support and maintenance team runs the system. The escalation path is written into the engagement and ends at a named person. Who leads Webaroo is on the team page.
On your side, two people: a backlog owner who can say yes, and the approver named on each gate. In a finance operation that is usually the controller or the operations lead.
What we run after launch
Monitoring
Smoke checks, error triage, and payment reconciliation, with alerts to your Slack. Illustrative: a nightly job matches every charge in the payment processor to the ledger and posts the mismatches, with amounts, before your team starts the day. A named person on the support and maintenance team owns each mismatch until it is closed.
Evals
A fixed set of real cases, re-run after every change. Illustrative: forty past invoices with the correct vendor, amount, and PO match written next to each. If extraction accuracy drops on that set, the change does not ship.
Model updates
Model providers retire and replace models on their own schedule. We test the new model against the eval set first, and it switches in only when it passes.
Cost control
Model spend is tracked every month and reviewed with you at the quarterly review. Each workspace has a spend cap, and the owner you name is alerted before it is reached, not after.
The approval queue
Anything the system does that moves money, contacts a customer, or changes production goes through an approval step owned by a named person. Illustrative: a vendor payment above the limit you set waits for the controller, with the extracted invoice and the match to the purchase order beside it. Every agent action is logged, so you can audit what ran and why.
The support and maintenance team reviews the approval queue. Each exception becomes a rule or a fix. This is how the system gets better after launch instead of worse.
The paper trail
Every production deploy is logged: what changed, who shipped it, when, and the written rollback that existed before it went out. Each quarter we review with you what shipped, what broke, and what we would do differently.
The cadence
A one-page executive briefing every month. A quarterly review. The pod's first measurement is its production checkpoint, at day 90 for a small pod or day 120 for a large pod: Day 90: what a production checkpoint means explains it. The shared backlog sets scope: if work is not in it, it is added in writing before anyone starts.
What you own
The accounts, the repositories, and the credentials. The runbooks your own team can follow: deploy, rollback, restore a backup, rotate a secret, and what to do when the system is down. Your team can cut off our access in one step. Network security, IAM and endpoint security remain the exclusive responsibility of your team or your MSSP. An MSSP is a managed security service provider. The security page covers how we handle your data.
Vluxure: Webaroo built the member platform and runs the technology behind the club.
When it does not work
It does not work when nobody on your side owns the backlog or reads the morning check. Then the alerts are noise and the queue only grows.
Where to start
If you have a system in production and nobody is on call for it, the paid assessment delivers an AI inventory, risk tiers, the top 3 workflows with today's numbers and a 90-day plan. For a straight answer first, ask Roo, Webaroo's AI: Who should run our AI after it goes live?
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