Learn

The category in one page. What these companies buy, why ownership is the distinguishing move, who the main actors are, and how to read the evidence labels you will see throughout the site.

The argument for why owning service businesses became an attractive way to deploy AI, as made by the investors who fund the category, and what would have to be true for it to hold.

Six provisional models separate who owns the vehicle, what it buys, how long it intends to hold, and whether the technology is shared. Most disagreements in the public debate are really disagreements about which model is being discussed.

The operating loop as the companies describe it, step by step, with the specific practices the research has been able to document and the ones that remain undisclosed.

The value-creation arithmetic behind the thesis, the metrics that would actually test it, and the definitional traps — committed versus drawn capital, gross versus EBITDA margin, run-rate versus recognised revenue — that the research refuses to collapse.

Accounting, legal, IT services, customer experience, property management and insurance each have a different shape of work, regulation and ownership constraint. The research is strongest in US and UK services; several sectors are coverage gaps rather than proven empty markets.

The strongest public objections to the thesis, attributed to the people who made them, organised by the kind of failure each predicts. A newcomer should leave this chapter able to say what would falsify the model.

Terms used across the site, from the category's own vocabulary (refounding, Creation, forward-deployed engineer) to the research's evidence and transaction labels.