From signal to production intelligence.
A structured engagement model with clear stages, gates, and shared accountability.
Four stages to production
Each stage has defined duration, deliverables, and exit criteria. No stage is skipped.
Discovery
Signal mapping and readiness assessment. We identify where AI delivers the highest-value outcomes.
- Signal inventory and data audit
- Readiness scorecard
- Recommended capability stack
- Risk and constraint map
Pilot
Controlled deployment of one capability against real signals with measurable success criteria.
Scale
Multi-capability system with monitoring, integrations, and operational hardening.
Production
Full system with continuous improvement, drift detection, and performance optimisation.
Discovery
2 weeksSignal mapping and readiness assessment. We identify where AI delivers the highest-value outcomes.
- Signal inventory and data audit
- Readiness scorecard
- Recommended capability stack
- Risk and constraint map
Pilot
4–6 weeksControlled deployment of one capability against real signals with measurable success criteria.
Scale
8–12 weeksMulti-capability system with monitoring, integrations, and operational hardening.
Production
OngoingFull system with continuous improvement, drift detection, and performance optimisation.
Success criteria and gates
No stage advances without meeting defined criteria. Gates ensure quality and alignment.
Collaboration model
Clear ownership. Shared outcomes. Your domain expertise meets our intelligence engineering.
Your team
- Domain expertise and context
- Data access and governance
- Stakeholder coordination
- Acceptance criteria
Our team
- AI engineering and architecture
- Model selection and tuning
- System integration
- Performance optimisation
Shared
- Monitoring and observability
- Iteration and feedback loops
- Success measurement
- Continuous improvement
Start with a controlled pilot.
2 weeks to first signal. 6 weeks to working intelligence.