We build self-improving models of your hardest domains, and the expert signal, environments, and verifiers they recursively grow from, taking each one past its ceiling.
A model trained on its own outputs can only rediscover what it already contains. It maps its boundary; it never moves it. Pushing the frontier takes signal a model can't generate alone, and that signal is what we make.
Founded by a team of researchers from Stanford, Berkeley, and other leading universities and frontier AI labs, with hands-on experience across the full foundation-model stack.
We build the expert signal, environments, and self-improving loop that take it past, for a model, a domain, a goal.
For inquiries, reach us at contact@ancest.ai