From AI pilot to production.
For organisations that want AI to deliver measurable results, and for software companies building AI into their products.
AI that works
in production.
Results like these come from the foundation, not the model: the right workflow, clear ownership and human oversight where it matters.
Three reasons AI pilots
never reach production.
Foundation first,
then the build.
The order matters. Teams that start at step three end up with tools that have no system to land in.
Map the real processes, the workarounds and the knowledge that lives in people’s heads. You cannot design AI for a process you only think you understand.
Define roles, handoffs, oversight and KPIs for the AI-augmented state before any code is written or prompt is engineered.
Now the technology lands in a system designed to receive it. The build is fast when the foundation is right, and it keeps delivering after launch.
Nine dimensions of
AI readiness.
Applied at the right depth for your organisation's size and stage.
Four ways I help
with AI.
Most AI pilots stall because the foundation was never checked. I assess your data, processes, operating model and team readiness, then identify and rank the AI opportunities worth pursuing by business value and feasibility.
Get Started →- AI Opportunity Assessment
- Data & Process Readiness
- Use-Case Prioritisation
- Operating Model Design
- Success Metrics & KPIs
- Executive Alignment
- AI Readiness Assessment
- Prioritised Use-Case Portfolio
- AI Roadmap
- Executive Briefing
I have shipped AI agents into production that cut manual effort by roughly 40% and noise in the workflow by over 90%. I help teams find the workflows where agents genuinely reduce workload, design them with the right human oversight, and take them from pilot to production.
Get Started →- Workflow Selection
- Agentic Workflow Design
- Human-in-the-Loop Controls
- Tool & System Integration
- Pilot-to-Production Rollout
- Outcome Measurement
- Agent Use-Case Shortlist
- Agent Architecture
- Pilot Plan & Success Criteria
- Production Rollout Plan
Choosing between building in-house and licensing a model or platform is an economics question, not a feature checklist. I model cost per customer and per run against margin, and set up the governance (ownership, usage policy and oversight) that lets AI scale responsibly.
Get Started →- Build vs. Buy Analysis
- Model & Vendor Selection
- Cost-per-Run Economics
- AI Usage Policy
- Ownership & Oversight
- Regulatory Readiness (EU AI Act, NIST AI RMF)
- Build-vs-Buy Business Case
- Vendor Scorecard
- AI Governance Framework
- Recommendation Memo
For SaaS and enterprise software companies adding AI to their products. I help define where AI creates real customer value and differentiation, how to package and price it, and how to get it from roadmap to adoption.
Get Started →- AI Product Vision
- Customer Value & Differentiation
- AI Feature Roadmap
- Pricing & Monetisation
- Go-to-Market
- Product Team Coaching
- AI Product Strategy
- Executive Roadmap
- Monetisation Model
- GTM Plan
Find out where you
actually stand with AI.
The same nine dimensions apply whether you're a 20-person startup or a 10,000-person enterprise. The depth changes. The sequence doesn't.