We reduce your risk before we build
Most AI projects fail not because the model is wrong, but because the problem was never properly scoped. We fix that first.
Not sure where to start? Ask us →
Fit call → Design Sprint → Build & Handover
Three stages. Each one earns the next.
Fit call
This is not a pitch. It's a listening session.
We start by understanding your situation—what you're trying to achieve, what you've already tried, and what constraints you're working within. If we're not the right fit, we'll tell you and point you to a better path.
The goal is clarity: is the problem real, is it solvable, and should we be the ones solving it?
What we explore together
- What problem are you solving and for whom?
- What have you already tried?
- What does success look like—and by when?
- Is your data accessible and usable?
- Who owns this problem internally?
- What are the security, budget, and timeline constraints?
Design Sprint
Reduce risk by making the solution tangible—fast.
If the fit call confirms the problem is real and solvable, the fastest way to reduce risk is to build something you can interact with. This is a paid, engineering-first sprint — not a slide deck exercise.
By the end, you'll know exactly what the solution looks like, what it takes to ship, and whether it's worth building.
You leave with
- A functional prototype — your team can interact with and validate
- Architecture & approach — how the system should work, and why
- Delivery milestones — what we'll ship, in what order, and how we'll measure it
- ROI model — a clear picture of the expected return
Build & Handover
Ship the outcome. Transfer the ownership.
We build in slices, integrate early, and measure against the outcome you care about. You see progress in working software and concrete milestones—not status updates or slide decks.
Our goal is not dependency. Our goal is ownership.
What you get at the end
- Production codebase — tested, documented, deployed
- Ops documentation — for using, deploying, and monitoring
- Training session — so your team can run it without us
Why this works
Most AI projects don't fail because of models. They fail because of everything else.
Unclear success criteria
We define measurable outcomes before writing a line of code.
No problem owner
We identify and work with a single decision-maker from day one.
Data not ready
We assess data access and quality in the fit call—not after kickoff.
Unrealistic timelines
The design sprint proves feasibility before committing to a full build.
Start with a conversation
Book a discovery call and we'll listen first, then recommend the fastest path forward.
Not sure where to start? Ask us →