Managed AI Services
Launch is the start, not the finish. We monitor, evaluate, maintain, and optimize your AI solutions so they stay accurate, secure, and valuable as your business changes.
AI systems change after launch, even when nothing else does.
Quality drift
New data, products, and policies gradually make answers and decisions less accurate.
Model changes
Providers update and retire models, affecting behavior, speed, and cost.
Growing costs
Usage grows and inefficient prompts or architecture become expensive.
No one owns it
Once the project team moves on, improvements and issues have nowhere to go.
Keep AI performing in production.
Monitoring & alerting
Track accuracy signals, errors, latency, usage, and spend, and respond when something changes.
Continuous evaluation
Re-run evaluation sets and review samples of real interactions to catch regressions early.
Model & prompt maintenance
Test and roll out model upgrades, prompt changes, and configuration updates safely.
Knowledge & data upkeep
Keep sources, indexes, and integrations current as your content and systems evolve.
Cost optimization
Right-size models, add caching, and streamline architecture to control running costs.
Improvement roadmap
Prioritize enhancements and new use cases based on usage and feedback.
How managed services work.
Onboard
Review the solution, agree success measures, and set up monitoring.
Operate
Watch performance, handle issues, and keep integrations healthy.
Review
Share regular reports on quality, usage, and cost with recommendations.
Improve
Deliver agreed enhancements and extend to new workflows.
Learn more about Improve
Who it’s for.
Solutions we build for you
Continue with the same team after launch.
AI built by others
Hand over an existing AI system for assessment, stabilization, and ongoing care.
Teams without in-house AI operations
Get specialist support without building a dedicated AI operations function.
Questions about managed AI services?
Can you support AI systems built by another team?
Yes. We start with an assessment of the existing system, then agree what needs stabilizing before ongoing support begins.
What does a support agreement include?
Scope, service levels, reporting, and improvement capacity are agreed with you based on how critical the solution is.
How do you handle model updates from providers?
We test new or changed models against your evaluation sets before switching, and roll back if quality drops.
Will we get visibility into performance?
Yes. Regular reports cover quality, usage, cost, and recommended improvements.