Worlds
World models can be built anywhere there is a changing world to learn. These are the first places we have worked, not the last.
Worlds for work
Clinical and regulatory development
Life Sciences
Follow a drug program through trials, submissions, approvals, label changes and withdrawal risk.
Current work: Project Confirm forecast FDA oncology outcomes across 3,275 held-out windows from drug programs the model had never seen.
Repositories and AI work
Software
Learn how work moves through a repository or an agent team, then predict what needs attention next.
Current work: Project OSS learnt from 7.04 million events and transferred zero-shot to a ninth repository. World Router uses the same idea to allocate AI work.
Anomaly and threat discovery
Cybersecurity
Learn what normally happens across a system so the few events that matter stand out from the millions that do not.
Current work: one model evaluated 1.1 million events and surfaced the 250 most unusual at 94% accuracy.
Worlds to play
Playable worlds
Games
Let a learnt model judge how each move changes the state of a game, rather than scripting every consequence in advance.
Current work: Mandate of Heaven turns six years of real AI history into a strategy game judged by a world model trained on 10,066 events.
Stories and invented worlds
Fiction
Model the state of a story so authors and agents can ask what is building, what comes next and what a change sets in motion.
Current work: Torus models a 100-scene manuscript. Star Wars and Middle-earth provide fresh fictional worlds for hidden-future tests.
The worlds are different. The underlying job is the same: build the record, learn how its state changes, and ask the model what happens next.