AI Engine BUILD & RUN — Implementation, Acceptance & Production Support
Give business and operating teams a tested workflow, a controlled release and clear ownership of performance, incidents and improvement.
Value to the engagement
A usable workflow with accountable operation
Who this helps
Process owner and users, engineering, IT release owner and support team
- BringAgreed design and controls
Acceptance criteria, access and operating owners
- Work throughBuild, test and release
Representative cases, business review and recovery plans
- Leave withOperate and improve
Monitor results, resolve issues and review benefits
Why this stage matters
BUILD & RUN implements the agreed design and tests the workflow with the people who will use and support it. Testing covers normal paths, business exceptions, system failures and, where relevant, AI output quality.
Release is followed by the agreed stabilization and handover activities. Ongoing support may sit with your team or with a separately scoped managed service. Production measures are compared with the baseline so improvements and remaining manual work are visible.
Who uses the output, and how
- Process owner and business users
- Validate the workflow on representative cases and review observed results against the baseline.
- Engineering and IT release teams
- Deploy with reviewed test evidence, access checks and recovery arrangements.
- Support and operations
- Take ownership with monitoring, exception procedures, escalation contacts and known issues documented.
How implementation becomes operational value
- Build and verify the workflow: Implement agreed components, integrations, controls and logging. Maintain test evidence as changes are reviewed.
- Obtain business acceptance: Use representative normal and exception cases with business reviewers. Record output quality, recovery behavior, outstanding issues and acceptance decisions.
- Prepare a controlled release: Confirm permissions, monitoring, deployment steps, rollback or manual fallback, and the people who authorize and support the change.
- Stabilize and review actual results: Track agreed measures such as manual touch time, completed transactions, exceptions and queue age. Compare observed results with baseline assumptions and agree follow-up actions.
A release is not proof of savings
Agree the observation period, data sources and benefit owner. Report measured outcomes separately from projections, including residual manual effort and operating costs where relevant.
What you leave with
The handover makes the released workflow and its operating responsibilities reviewable:
Deliverables and acceptance criteria are confirmed in the engagement scope.
- Release package and acceptance record: Versioned implementation, test and evaluation evidence, business acceptance, open issues and release approval.
- Operations and recovery runbook: Monitoring, exception handling, incident escalation, coverage, maintenance responsibilities and rollback or manual fallback procedures.
- Stabilization and benefit-review record: Observed performance against acceptance criteria and baseline measures, with remaining issues, accountable owners and agreed improvements.
Invoice processing after launch
Starting situation: Successful bot runs are reported, but the team does not know whether manual rework or queue age has improved.
Useful output: Operations reviews completed transactions, exceptions and manual touch time against the baseline, with named owners for defects and process improvements.
An example of how the stage can be used, not a client result or a promised outcome.