Project 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.
Phase 1 — Diagnose & Decide
Independent root cause analysis of the failing initiative. The output is a fix-or-kill verdict backed by evidence, not opinion.
AI Project Rescue Diagnostic
A principal-led diagnosis of a failing AI initiative — with an honest fix-or-kill recommendation.
- Stakeholder Interview Summary
- Architecture & Approach Review
- Root Cause Diagnosis
- Fix-or-Kill Recommendation
After: Root cause analysis complete. Fix-or-kill recommendation delivered with a recovery playbook if the verdict is fix.
Phase 2 — Redesign & Correct
If the verdict is fix: the architecture that caused the stall is replaced with a build-ready specification the delivery team can execute against.
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 specification the dev team can execute from day one. The architecture that caused the stall is replaced.
Phase 3 — Oversee & Hold
The same principal who diagnosed the problem stays engaged through the rebuild — sprint-level architecture reviews, decision support, 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 diagnosed the problem stays involved through the fix.
Outcome
Initiative back on track — or cleanly shut down.
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 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 journeyLegacy Modernization
A company with a 10-20 year old estate — monoliths, legacy platforms, half-finished migrations — needs AI capabilities, but every initiative stalls on integration complexity. Vendors pitch solutions that assume modern APIs and clean data. Neither exists.
View journeyReady to start the Project Rescue journey?
Book a 30-minute discovery call. We will listen to your situation and confirm the right starting point — no commitment required.