AI Architecture
Budget for an AI build has been approved. But no one internally has the combination of system-level architecture experience and independence from the vendor proposals on the table — and development is about to start without a blueprint.
Phase 1 — Assess & Sequence
OptionalIdentify which AI opportunity to build first — scored against business impact, data readiness, and integration complexity.
AI Opportunity Assessment
A structured, workshop-driven engagement that identifies, scores, and prioritises AI opportunities across your business — and hands you a roadmap you can act on immediately.
- AI Opportunity Register
- Feasibility Scorecard
- Prioritisation Matrix
- Business Case Summaries (Priority Opportunities)
After: Top AI opportunity selected with business case. Sequencing defined for what follows.
Phase 2 — Design & Specify
Produce a build-ready architecture the development team can execute from day one — technology stack, data strategy, AI pipeline, integration patterns, team specification, and vendor evaluation criteria.
AI Solution Architecture & Design
Complete solution architecture for an identified AI opportunity — technology selection, integration design, data strategy, team specification, and governance framework. Build-ready output an engineering team can implement from day one.
- Solution Architecture Document
- Technology Selection Matrix
- Integration Design
- Data Strategy & Pipeline Design
After: Build-ready architecture with stack, data strategy, AI pipeline, and team spec. Everything needed to start building without guesswork.
Phase 3 — Oversee & Govern
The same principal who designed the architecture stays engaged through the build — sprint reviews, quality gates, vendor evaluation, and drift detection.
Principal Architecture Oversight Retainer
Ongoing architecture governance and decision support for active transformation programs.
- Monthly Architecture Review
- Decision Log
- Risk Register Updates
- Architecture Board Facilitation
After: Every sprint reviewed. Architecture drift caught early. The same principal who designed the system stays accountable through delivery.
Outcome
Build-ready architecture delivered, team guided to first release.
Related Journeys
First AI Build
A company needs its first AI use case in production — not a strategy deck, a working capability. There is no internal AI team, no data science function, and no prior AI initiative to build on. Every vendor wants to sell a 12-month programme. The pressure is to show proof of value before committing at that scale.
View journeyProject Rescue
An AI initiative is behind schedule, over budget, or stuck in pilot — and nobody internally has the independence or the mandate to say whether it should be fixed, restructured, or killed.
View journeySecond Opinion
A significant architecture decision or investment is on the table — new AI platform, vendor selection, build-vs-buy — and leadership wants independent validation before committing budget.
View journeyReady to start the AI Architecture journey?
Book a 30-minute discovery call. We will listen to your situation and confirm the right starting point — no commitment required.