Every project starts with metrics, not tools
Work runs in four phases, and each ends with a decision point, so you never commit a large budget before seeing results.
MeasuredDecide phase by phase
Four phases, four decisions
Every phase ends at a decision point. You go on when results meet the bar, and can stop without committing the next phase's budget.
01
Discovery
Map your data, systems and processes, pick the use case with the best return, and agree on the metrics.
Deliverables- AI opportunity map
- Data readiness report
- Baseline metrics
- Roadmap and investment plan
Led by
Decision point
Is this the right problem to start with, and how will it be measured?
When each discipline is involved
How a typical project is staffed. Every discipline is on the team from the start, and the lead changes with each phase.
| Discovery | Pilot | Production | Scale | |
|---|---|---|---|---|
| AI Agent | Supports | Leads | Supports | Supports |
| Cloud Native | Supports | Leads | Supports | |
| Security | Supports | Leads | Supports | |
| Architecture | Leads | Supports | Supports | Leads |
| Engineering | Leads | Supports | ||
| Business | Leads | Supports | Leads |
Leads Supports
Ways to work with us
Start small and grow. Use the readiness check to see where you should begin.
Readiness assessment
A short, fixed-scope engagement that ends with a readiness report and prioritized use cases.
Pilot
A fixed-scope build of one use case on real data, measured against the agreed metrics.
Build
Take the system to production following the plan from the pilot.
Retainer
Ongoing support, improvements and new use cases.
Yours to run
What you get on every project
- Architecture documentation
- Source code you own
- Runbooks for operating the system
- Training for your team
Find out how ready you are for AI
Answer 13 questions in about 5 minutes. You get a readiness score across 6 areas and a first scope to start from.