From AI ambition to AI in production
Built and shipped by operators.
Outcomes over advice.
Enterprise AI rarely fails on the model
It fails in the weeks after launch, when the new way of working meets the old one. The reasons are predictable, and avoidable
The tool arrives before the problem
A tool chosen before the work is understood will find a workflow to fit. It rarely reaches the bottom line.
AI is bolted onto a process nobody redesigned
A bolt-on inherits every constraint of the process beneath it. The ceiling is set before you begin.
The company builds what it should have bought
Undifferentiated capability is cheaper bought than built. Spend the build budget where you are actually different.
Digital transformation changed the systems. AI transformation changes the decisions.
Build, deploy, adopt: hand in hand
In our experience the model is rarely the hard part. Most of the work is finding where the process breaks, rebuilding the workflow around it, and staying while your team learns to run it without us. The people who scope that work are usually the same people who build it.
What we bring
A product we built and run ourselves, a way of finding where the value sits, and the transformation work that follows. The same senior team across all three.
We have seen technology built end to end
Founded, scaled and exited technology companies, and backed others doing the same. It is why we start by building
The people who scope it are the people who build it
No handoff between the strategy and the system. The same team is on both
Let's get you to production
We'll give you a straight read on where AI lands, and where it doesn't
Book a short discovery call to get started