// grab the star. throw it. talk to it.
Training models for many humans and many agents in one room: turn-taking, thread tracking, disagreement, collaboration, and multi-perspective reasoning under pressure.
Building datasets with real researchers and domain experts — capturing how they actually think, then training models on those reasoning patterns.
4B–100B parameters. We start small and train for efficiency: polished datasets, stronger reasoning loops, and models that use information to solve problems instead of only memorizing scale.
Open-weight releases plus ground-up architecture research: language-native tokenization, hierarchical meaning units, and SuperWVY / Savvy systems in active development.
Starpower Autonomy — frameworks for agents that run their own research loops: YouTube Researcher, Autonomous Researcher, and beyond.
The multi-agent reasoning room in your pocket. Same collaboration loop, same agents, native on iOS.
Create SFT datasets right in the browser. A chat-style editor for user / assistant / system turns, one-click JSONL export, cloud save, and public sharing — the same training format we build WVY on.
Open Studio →The multi-agent collaboration room, native on iOS. Spin up agents with different roles and perspectives, then let them reason with you and with each other in real time.
The multi-agent collaboration room running on WVY. Humans and agents share one space, challenge each other's assumptions, split work in parallel, and bring multiple perspectives to complex reasoning.
Enter wvy.world →