Three founders, covering exactly what this takes to get right.

Every company we walk into is already using AI. Almost none of it is running where the business actually happens. It lives in browser tabs, in personal accounts, in a prototype somebody built on a Friday. Useful, invisible, and impossible to answer for.

The cost of building software collapsed. The cost of trusting it did not. A company can generate a thousand lines of code in an afternoon and still take six months to let any of it touch a customer, because nobody can say who owns it, what it read, or what happens when it is wrong.

That gap is not a talent problem or a budget problem. It is that no one owns the boundary between what an AI can do and what a company can defend. Engineering cannot review everything. The areas that understand the work cannot ship on their own. So the good ideas stay demos.

We think AI inside a company is an operating problem before it is a technology problem. It needs the same things any serious system needs: an owner, a version, a way to measure whether it worked, and a way to turn it off. Give people those, and the teams closest to the work turn out to be the ones who build the best of it.

We have built and run systems at Uber, Mercado Libre and at companies we founded ourselves. The domains change; the pattern does not. Capability that lives with an outside team leaves when that team leaves. Capability installed inside a company compounds.

So we build the layer that lets a company's own people put AI to work, and stand behind what it does.