Why finance was last
Four operating systems shipped before this one. That order was not an accident of staffing.
The obvious way to build a finance product in 2023 was to build a finance product. Point a language model at statements and filings, wrap it in a dashboard, ship. Several companies did exactly that, and the results were competent at the thing that was never the bottleneck.
Valuing a contested claim is not a finance problem wearing a finance hat. Consider what actually has to happen before a number is defensible. Somebody has to read a treatment record and decide whether the care was clinically coherent or whether a defence expert will take it apart. Somebody has to read a lien filing and decide whether the security is perfected in that jurisdiction. Somebody has to know how a particular counterparty behaves when it is time to pay, which is not in any document. Only then does anyone discount anything.
Three of those four are not finance questions. A finance product built first would have had to approximate them — which in practice means a single model asked to hold four kinds of expertise at once, producing an answer with no attribution and no way to tell which of the four readings was the weak one.
So Chiron, Justine and Issac were built first, and Eli is built on them. That is why the family page on this site is load-bearing rather than a credibility badge: the medicine, the law and the counterparty analysis in a valuation are the same specialists that serve their own verticals. The composition is not a marketing story about shared infrastructure. It is the reason a number here can carry a citation at all.
The corollary is the part worth sitting with. If you are evaluating a finance AI product, the question is not how good its model is. It is which of the four readings it is faking.