Enact

The post-training layer for physical AI.

[Enact @enact_labs]

@lancectk Glad to be working with you!

[James Stevens @jamesw_stevens]

We’ve started moving onto longer-horizon tasks.

Table bussing - π0.5 completed 48/50 rollouts on a consistent setup. Very much in distribution, but a useful baseline.

[Jon Xu @xuster]

Base models for robots are improving but the hard part is always the last mile. @enact_labs is the post-training infra that's been missing to get robots to do reliable work in the real world. Very impressed with what @jamesw_stevens and @govindchada have built. Congrats on the launch 🚀

[Govind Chada @govindchada]

after years of babysitting robots in the gates basement at stanford, i’m proud to finally share what we’re building at @enact_labs

[James Stevens @jamesw_stevens]

Today we’re launching Enact: post-training infrastructure that makes robotics models work in the real world.

Robotics models fail when execution reaches states their training data never covered. A slip, an off-angle grasp, or an external disturbance can leave the policy without a learned recovery.

Enact finds those failures and generates the targeted recovery data teams use to make their models reliable in production.

@govindchada @enact_labs