How useful AI is inside a company is three factors multiplied:
The first factor you rent. Everyone gets the same models.
The other two have to be built. They’re specific to your company, and in most companies today they’re close to zero. It doesn’t matter how large the first number gets. Anything multiplied by zero is zero.
We build and deploy the other two.
The four levels
AI adoption climbs a ladder:
Almost every company is stuck between one and two: an immensely intelligent brain, rented for a few hundred dollars a month, drafting emails and summarizing calls. The usual conclusion is that AI isn’t ready for serious work. But that’s using a jet engine to blow-dry hair. The model was never the constraint. The other two factors are near zero.
Levels three and four are the two factors you can’t rent. They’re what we build.
Understanding
Hire someone brilliant and they’re still useless for months, even with access to everything on day one. What they build in those months is a map: what exists here, how it relates, why things are done the way they are. That map lives in heads, and no model can use it there.
We build that map so it lives outside of heads, and we build it as structure rather than documents. Every customer, product, promise, risk, and rule exists exactly once and is connected to what it touches. Every fact traces back to its source and stays current from the tools where the work happens. When an agent looks at an account, everything attached to it is just there. The old name for this kind of map is an ontology.
It’s also why AI got good at writing software before anything else: code is the one part of a company that was already written down.
Action
Workflows are the wrong primitive. A workflow is a decision made once and repeated forever. That was the only way to automate when software couldn’t think. But software can think now, so we should stop handing it steps and start handing it the outcome.
So we give agents jobs instead: the outcome, the part of the world they work in, and the actions they can take. You decide what an agent can do on its own and what needs your approval, and widen that as it proves itself.
A job also outlives the chat it started in. It keeps its state, evidence, and decisions as models and agents come and go, and leaves what it learned on the map for the next one. Your company will end up using many agents, and jobs are what make them work as one company.
Who this is for
A simple test: how long does it take a smart new hire to become useful?
If the answer is day one, your business is simple enough that a frontier model with a few tools already does good work. You don’t need us.
If onboarding takes months, your business is genuinely complicated: supply chain planning, security, industrial technology… That’s where the gap between what models can do and what companies get from them is widest.
Those are also the companies that will last. Horizontal software will be reproduced by AI faster than anyone likes to admit. A deep domain moat is knowledge, context, and method, not code. AI compounds that moat, for the companies that make themselves usable by it.
Sooner or later, every company will be an AI company at its core, the way every company became an electricity company and then an internet company. Becoming usable by AI is how you get there.
If this described your company, reach out.
Reach out