Jigsaw is an applied research lab scaling the creation of simulated environments.

The final primitive for superintelligence is learning through simulated environments. That is how models became strong in coding and math. The next frontier is the rest of human labor and interests.

Today, model progress is constrained by a shortage of realistic learning environments. RL environment creation remains largely hand-built and labor-intensive, with each new domain requiring bespoke world, task, and eval design. The supply of new environments is growing too slowly to meet demand from frontier labs, neo-labs, and experimental open-source teams.

We train foundation models and build systems for world generation, authoring, and evaluation, enabling high-fidelity environments that transfer human expertise into model capability. Over time, Jigsaw aims to become the infrastructure layer for creating, serving, and accessing simulated environments across any domains.

Our long-term ambition is to power the world's most extensive repository of environments and simulations for fine-tuning and evaluating models.