How we work
Evidence before scale.
We do not begin by assuming AI is the answer. Each stage ends with a decision, and you only move on when the evidence supports it.
The four stages
Stage 1
Understand
Is this problem worth solving?
- What happens
- Map the process, people, data and economics; set the baseline.
- What you decide
- Whether the problem justifies further work.
Stage 2
Define
What intervention would change the outcome?
- What happens
- Specify scope, dependencies, risks, costs and success criteria.
- What you decide
- Whether to test it, and against which criteria.
Stage 3
Validate
Does it work well enough here?
- What happens
- Build or test only enough to answer the key questions; measure against the criteria.
- What you decide
- Stop, refine or implement.
Stage 4
Realise
How do we make it operational and keep it working?
- What happens
- Implement, integrate, put controls in place, train people, measure.
- What you decide
- Whether the measured result holds in live use.
Commitments
What you can expect from us.
- Success criteria are agreed in writing before anything is built.
- Costs and scope are fixed for each stage before it starts.
- We will recommend stopping when the evidence says stop.
- Governance and data protection are designed in from stage 2, not added at the end.
- Deliverables made specifically for you are yours, as set out in each statement of work. We keep our own methods, tools and reusable components.