We run an AI-native group of operating companies. The judgment we sell an enterprise or an investor is the same judgment we spend on ourselves every week. That is the whole argument.
Our point of view
Almost every enterprise now has an AI ambition and a slide to prove it. Very few have turned that ambition into a capability that ships and pays for itself. The gap is rarely the model. It is sequencing, org design, and the discipline to carry an idea from a demo to production. We start from the operating model and work back to the technology, because that is the order in which value actually appears.
A generic scorecard tells an investor a codebase is a "3 out of 5." It does not tell them whether the architecture survives the next scale phase, whether the team can execute the plan they are being priced on, or which risks are worth walking from. We write diligence for the decision in front of you: invest, walk, or renegotiate. The deal-moving risks are named plainly, and the cost to fix them is on the page.
Frameworks are portable; consequences are not. When we tell you where to place an AI bet, it is because we are placing the same bet with our own companies and living with the result. When we assess a team for an investor, it is because we have led teams through exactly the wall they are about to hit. Advice earned in production travels. A template does not.
“Most technology advice is written by people who left the arena years ago. Ours is written by people still in it.”
What we practice
A sequenced roadmap your teams can execute, and the delivery discipline to keep it moving from demo to production.
Team topology, hiring, and delivery practice shaped so the org compounds instead of clogs. The playbook that ran 500-plus engineers at Adidas, adapted to your stage.
Product, architecture, and team assessed against the thesis and the price. A decision-ready read, fast enough for a live process.
Operator-level technology judgment in the room when you need it, without a full-time hire. Board prep, a critical build, a turnaround. Accountable to the outcome.
Questions readers ask
Two things that reinforce each other: we help enterprises design and execute AI strategy and digital transformation, and we run technology due diligence for private equity firms, venture investors, and founders. The same people who build and run engineering organizations are the ones who assess them for investors.
Thomas Prommer, our Group CEO and CTAIO, leads advisory personally. He was Global SVP of Engineering at Adidas (500+ engineers), CIO at Sweetgreen, and Senior Technology Advisor at Bain Capital. You get operator judgment, not a slide deck from someone who has never shipped.
Due diligence is written for a decision — invest, walk, or renegotiate. We assess the product, the architecture, and the team against the thesis and the price, then hand you a clear read on the risks that actually move the deal, not a generic maturity score.
No. Enterprises come to us for transformation; investors and founders come to us for validation. Engagements scale from a focused two-week diligence sprint to a multi-quarter transformation program.
Start here
A build to get right, a transformation to sequence, or a deal to de-risk.
Get in touch