Our method: from scoping to production

The problem we've seen too many times

A company launches an ambitious AI project, signs a six-month fixed framework contract, and discovers in month four that the use case isn't feasible as planned — or that inference costs make the ROI negative. By then, the budget is spent, the internal team has disengaged, and the project closes with no usable deliverable.

Our answer: commit in phases, validate at each step

Each phase is short (2 to 6 weeks), with a concrete deliverable and a binary decision at the end: continue, pivot, or stop. You commit the budget for the next phase only if the previous one delivered on its promises.

Why it works

Three things change compared with a classic framework contract:

1. The go/no-go is explicit and written. You know the criteria you're deciding on, not an end-of-meeting impression.

2. The scope is tight. A scoping phase doesn't try to do everything. It answers one question: is this project feasible, at what cost, with what expected quality?

3. Your teams are involved from phase 2. No surprise handover at the end. Your engineers have watched the code take shape and taken part in the technical decisions.

What if we want to move faster?

On projects where the business window is short (product launch, regulatory deadline), we can compress the phases while keeping the validation gates. What we never compress: the production-rollout phase. An AI system deployed too fast is an incident that ends up at the top of an executive meeting.

The phases at a glance

• Scoping — 2 weeks, fixed cost, no follow-on commitment
• Prototype sprint — 4 to 6 weeks, per-sprint package
• Production rollout — 3 to 9 months, day rate or fixed price, your choice

Details on the Engagement models page.