Production is the start of operational learning.
A Production Value Sprint puts a real workflow into production. Managed AI Operations then runs, monitors, improves, and governs it. Ownership can be Managed, Co-Managed, or Build & Transfer — never a free trial and never a public price list.
Run, Monitor, Improve, Govern, Expand.
The sprint ends at a Production Readiness Gate: functional, economic, quality, governance, and operational. If the gate is not met, the work is not in production.
After the gate, someone has to own the queue at 2 a.m. Alltera can operate that layer, share it, or transfer it with the runbook, evaluations, and decision rights intact.
Production Readiness Gate
Managed
Alltera operates coverage, quality, cost, and improvement.
Co-Managed
Client and Alltera share the queue, decision rights, and backlog.
Build & Transfer
Capability and runbook move to the client with a defined handoff.
How production is held after the first outcome.
Production Value Sprint
Fifteen to thirty days to a live workflow and the first measurable outcome.
Managed
Alltera runs the capability: coverage, quality, cost, and improvement cadence.
Co-Managed
Client operators and Alltera share the queue, alçada, and improvement backlog.
Build & Transfer
The capability, runbook, and library assets move to the client with a defined handoff — not an abandoned demo.
Runbook and exceptions
Hours, owners, escalation, and freeze conditions are explicit.
Continuous improvement
Skills, rules, and autonomy move only with evidence from live cases.
The first outcome is a gate, not a slide.
Map the workflow, then put it into production under an ownership model the risk can bear.