03 · Governed AI
Governed AI integration for workflows people can stand behind.
Production AI integration with explicit data boundaries, human review, evaluation, logging, versioning, and change control.
The problem
What this engagement needs to resolve.
A useful AI demonstration is not yet a production workflow with defined behaviour when an output is incomplete or wrong.
Deliverable
An AI-enabled workflow with defined inputs, outputs, review and escalation paths, supplier controls, evaluation criteria, and operational records.
Client input
A clear use case, representative examples, an accountable owner, and agreement on where human judgement remains mandatory.
Commercial shape
A clear starting point, then a responsible scope.
- Commercial starting point
- Bounded implementation may start around £7,500; substantial work is scoped around the workflow and assurance requirements.
- Duration
- Confirmed after the workflow, data, and assurance requirements are understood.
What is covered
The practical shape of the engagement.
The exact scope is agreed around the operational outcome, the systems involved, and the evidence needed to accept the work.
- 01
Document processing and extraction
- 02
Internal knowledge assistants
- 03
Human review and escalation
- 04
Evaluation and regression tests
- 05
Data and supplier boundaries
- 06
Logging and model change records
Scoping questions
Questions before assumptions.
- What information may the system see?
- What does a reviewer need to verify?
- How will a bad answer be detected?
- What evidence must the workflow retain?
What changes the scope
- Data sensitivity and source systems
- Evaluation depth and review design
- Model, supplier, and deployment choices
- Audit and change-management requirements
Related routes