We're solving the
open-ended data problem.
Fig is developing new scalable approaches that turn real open-ended, multi objective knowledge work into data and environments with consumable signals to train and augment frontier AI systems. Read more ↗
We're sharing early previews with select teams ahead of our upcoming releases. If you're deploying models into complex, open-ended environments, we want to hear from you.
The challenges in open-ended work
01
Evolving environments
Real desktops that can't be reset with evolving context from dozens of windows, tabs, and apps
02
Unscripted paths
Multi-thousand-step workflows spanning tens of hours without instructions, app clones, or fake data
03
Interruptions and distractions
Workflows that branch, stall, and resume as tasks are reprioritized and progress is made towards goals