Offer
Managed AI Operations
Without an operational owner, quality, cost, and autonomy drift. Production becomes a closed project.
- When to engage
- When the workflow is already in production and needs operations, monitoring, governance, and continuous improvement.
- Problem solved
- Without an operational owner, quality, cost, and autonomy drift. Production becomes a closed project.
- Scope
- Run, Monitor, Improve, Govern, and Expand for an AI-native workflow already in production.
- Duration
- Ongoing operational retainer while the capability remains in production.
- Client participation
- Workflow owner, an exceptions channel, and participation in autonomy and risk decisions.
- Commercial model
- Managed operations. Not a software subscription plan and not unbundled development hours.
- Deliverables
- Agreed operational coverage
- Observability of quality, cost, and throughput
- Improvement cycle for skills, rules, and exceptions
- Governance of access, models, and audit
- Next step
- An AI Transformation Pod when the organization is ready to expand across workflows.
Acceptance
Managed AI Operations
- 01Agreed coverage, owners, and freeze conditions.
- 02Quality, throughput, autonomy, and AI cost per outcome are reviewed on a set cadence.
- 03Improvements to skills and rules are evidence-led.
- 04Governance of access, models, and audit remains active.