Most organisations have run an AI proof of concept. Far fewer have one in production. The gap isn’t talent or technology, it’s also the absence of a structured delivery framework built for the realities of AI. The AIPDL is how dataengine closes that gap.
Every use case is stress-tested for feasibility, desirability, and business value before a single line of code is written.
No throwaway experiments. The proof of concept is architected for production from day one, eliminating rework and budget risk.
KPIs and baselines are defined at Stage 2 not after delivery. Success or failure is always objective, never assumed.
Capability transfer is a design principle, not an afterthought. Your team owns and evolves the solution without vendor dependency.
