Run and support
Managed AI Services
Oversight of what goes in and out of your AI systems. Integrations, APIs, cost and accuracy, watched monthly.
The problem
AI systems do not sit still. Models get deprecated, prices change, an integration starts failing quietly, and accuracy drifts until someone notices a wrong answer went out. Most firms have no one whose job it is to watch that, and the first sign of trouble is usually a client seeing it.
What we build
- Monitoring and alerting on accuracy, cost and availability
- Integration and API health, watched at the boundary where data goes in and comes out
- Model version management and migration when vendors deprecate
- Regular evaluation runs against your test set
- Cost review as usage and vendor pricing change
- A defined support path with response commitments
How the engagement runs
Monthly, priced by the number of systems watched and the response commitment you need. Smaller in scope and cost than Embedded AI Leadership, and separate from it: this watches the plumbing, that changes the business. It does not depend on who built the system.
What you get
- A monthly report on accuracy, usage and spend
- Version currency
- Alerts before a client sees the problem
- One accountable contact when something breaks
Where this does not fit
If you have no AI systems running yet, there is nothing to watch. Start with a build, or with Embedded AI Leadership if the question is what to do at all. And if you have internal capability and want to run it yourself, we will hand over properly and stay available ad hoc. This is not a lock-in.
Related solutions
- AI Reporting and Operational IntelligenceReporting that answers the question you actually asked, across the systems your business already runs on.
- AI StrategyWork out where AI actually pays in your business, and in what order to do it.
- Embedded AI LeadershipAn AI lead embedded with your leadership team, working on how the business actually runs.
Start with a discovery call.
An hour on how your business runs, where the time goes, and whether AI is worth spending money on yet. You leave with our written read, whether or not we build anything.