Problem
We do not know which models are in use or how risky they are.
We cannot explain a model's decision.
A regulator or customer is asking questions we cannot answer.
Outcomes
- A defensible governance position
- Clear oversight of models in use
- Evidence ready for scrutiny
Scope
In scope
- Model inventory and risk assessment
- Evaluation and monitoring setup
- Governance and oversight process
Not included
- Building the models (see generative AI)
- General data governance (see data strategy and governance)
Approach
Discovery
We agree the problem, the data and the constraints, and how success will be judged.
Delivery planning
We shape the approach, sequence the work and set out costs, risks and controls.
Build and test
We build in the open, test against real data and cases, and prove it before it goes near production.
Operational readiness, hypercare and closure
We hand over, support the first weeks of use, and confirm the outcome before we close.
Deliverables
Technologies
Controls
Frequently Asked Questions
Is this only for regulated industries?
No. Any organisation making decisions with models benefits from being able to explain and defend them.
Do you replace our risk team?
No. We give your risk and governance owners the tools, evidence and process to do their job.
Ready to scope this?
Tell us where your AI needs to stand up to scrutiny and we will help you get there.