Managed AI Operations
Shipping the AI system was the easy half.
Models drift, providers deprecate, costs creep, and the person who understood the retrieval pipeline just changed jobs. Production AI needs the same operational discipline as any critical system — and almost nobody has an MLOps bench sitting ready.
What are managed AI services?
Managed AI services operate your production AI systems as an ongoing service: monitoring quality and drift, re-running evaluations on every model change, controlling token costs, patching integrations, and responding to incidents under SLA. Mufasa Labs runs the systems we build — or takes over ones you already have — so you get the outcomes without staffing an operations team.
Who it helps
Built for teams under real deadlines
Teams without an MLOps bench
You want the AI system's results, not a new 24/7 operational responsibility.
IT leaders holding the pager
Someone accountable when quality dips or the provider changes an API overnight.
Companies scaling what works
The pilot succeeded; now it needs the operational rigor of a production platform.
In practice
We build it. We run it. You get the outcomes.
Models drift, providers deprecate, costs creep, and the person who understood the retrieval pipeline just changed jobs. Production AI needs the same operational discipline as any critical system — and almost nobody has an MLOps bench sitting ready.
What we deliver
What lands on your side of the table
Quality & drift monitoring
Dashboards and alerts on accuracy, resolution rates, and behavior drift — problems surface before users report them.
Evaluation on every change
Model updates, prompt changes, and provider migrations run the eval suite before they touch production.
Cost management
Token-level visibility, routing optimization, and caching — spend stays predictable as usage grows.
SLA incident response
Defined response times, runbooks, and a named engineer who already knows your system.
How it works
A process with no big-bang weekends
- 01
Onboard the system
We instrument monitoring, evals, and runbooks — for systems we built, this is already done.
- 02
Set the SLA
Response times, quality thresholds, and reporting cadence agreed and written down.
- 03
Operate & report
Monthly reports on quality, usage, cost, and incidents — with tuning applied continuously.
- 04
Evolve or hand off
New capabilities ship under change control; or we train your team and hand over the runbooks. No lock-in.
Outcomes
What good looks like
Why teams trust us
Proof over promises
- Run by the engineers who build these systems — not a ticket queue reading from a script.
- Everything stays in your cloud and your repos; the runbooks are yours, and handoff is always available.
- Month-to-month terms — the SLA earns its renewal with every report.
FAQ
Managed AI Operations: common questions
Can you manage AI systems you didn't build?
Yes. Onboarding starts with an audit and instrumentation pass — monitoring, an evaluation set, and runbooks — after which the system is operated to the same standard as ones we built ourselves.
What does the SLA actually cover?
Defined response times by severity, quality thresholds tied to your evaluation suite, provider-change management, and monthly reporting. The specifics are written per system — not a generic support tier.
Why does AI need ongoing operations at all?
Because AI systems degrade quietly: models drift, providers deprecate endpoints, content changes under retrieval, and costs creep. Without monitoring and re-evaluation, quality problems surface as user complaints instead of alerts.
How does pricing work?
A fixed monthly fee scoped to the system's criticality and complexity, agreed up front — no per-incident surprises. Month-to-month terms, and the fee typically costs a fraction of one operations hire.
Can we take operations in-house later?
Any time. Runbooks, dashboards, and evals live in your environment from day one, and handoff includes pairing time with your team. Managed operations is a service, not a hostage situation.
How to start
Book a 30-minute scoping call. You'll leave with an honest read on scope, timeline, and cost — whether or not you hire us.