AI & Data · Govern
Keep your AI performing, and delivering value, long after launch.
A production AI system is one that no longer surprises the business. We run yours like any other critical system, alongside the 24/7 monitoring, helpdesk and hosting we already provide for the platforms we build, and watch the things that are new with AI: quality and cost.
One dashboard, three columns.
Familiar
Uptime, errors and response times, watched 24/7 like any system we run, with alerts when they drift.
Quality
How often it escalates, how often a person overturns its answer, and whether its confidence matches how often it's right.
Cost
Forecast and actual, per use case and per step, so a change that quietly doubles the bill is caught in days, not at the invoice.
AI that is looked after.
Evaluation on a schedule
Your evaluation set run weekly against the live model and on samples of live work, with every real failure added to it.
Every change is a release
A change to the prompt, the data it reads, its tools, its thresholds or the model is tested before it goes live, like any other release.
Model changes, planned
The model version is pinned, so nothing changes underneath you. When a provider announces a retirement, the move is planned then, not when the date arrives.
Pause when quality drops
A fall below your threshold is a reason to pause, not to lower the bar, until the cause is found and fixed.
A runbook and an off switch
Written steps for the new ways AI can fail, someone on call, and a tested way to stop it at once.
An exit test
How long, and at what cost, to move to another AI provider, rehearsed at least once a year, so you know what a move would take.
Plan. Build. Govern.
Plan
Where AI pays, and in what order. For a whole business, the PureNet Group's Converge Methodology; for a single area, a fixed-scope assessment.
Build
A pilot with a number to move, an owner and a way to stop it, then production in your storefront, portal and back office, integrated with your ERP and CRM.
Govern
Govern the use, not the technology. Your own AI on business terms, with an owner, a one-page policy and an inventory; and every system we build for you tested on every change, logged, overseen by a person and fitted with an off switch, under our ISO 27001 controls.
What people ask us.
What happens if the AI starts getting things wrong?
Quality is watched like uptime. If it falls below the threshold you set, we pause the affected work, find the cause, fix it and add the failing cases to the evaluation set, so it is tested for from then on.
What happens when an AI provider retires a model?
Your system runs on a pinned model version. When a retirement is announced, we plan and test the move like any release, well before the date.
Can we move to a different AI provider?
Yes. We keep a record of how long and what it would cost to move, and rehearse it at least once a year, so you always know what a move would take.
How do you keep costs predictable?
We forecast the cost of each use case before it goes live and track it per step afterwards, so a change that pushes costs up is caught quickly.