Production AI needs operations, not just deployment.
The questions a deployment alone doesn't answer.
Recurring operations, not a one-time handoff.
Ongoing visibility into model and agent behavior in production.
Catch quality drops before they reach your users.
Track and control inference and infrastructure spend over time.
Keep permissions current as teams and systems change.
Manage provider and model version changes deliberately, not accidentally.
A defined process for when something in the AI system breaks.
Controlled releases with a rollback plan.
End-to-end visibility from workflow trigger to model response.
Availability depends on the agreed scope — we define response times and coverage explicitly rather than assume around-the-clock coverage.
In most cases, yes, after an initial architecture and access review.
Full documentation and knowledge transfer, so your own team can operate the environment independently.