ROBOTICS

Robotics & Embodied AI

Scale simulation-to-real training pipelines with elastic GPU capacity and reproducible, sandboxed environments.

Close the sim-to-real gap

Embodied AI needs millions of rollouts. Run massively parallel simulation environments on elastic GPU capacity, and scale policy training without rewriting your stack.

Deterministic sandboxes make every rollout reproducible, so regressions in the policy are traceable to changes in the environment — not to infrastructure noise.

From lab to fleet

Export trained policies with full lineage — environment version, reward spec, and evaluation results — ready for deployment on real hardware.

FIG. 01 / SETUP

48 h

From zero to a self-improving loop

FIG. 02 / ENVIRONMENTS

2,000+

RL environments ready to compose

FIG. 03 / OVERHEAD

0

Reward engineering required

PLATFORM

Everything this solution needs. None of the overhead.

1

Environments Hub

Compose repositories, toolchains, and test harnesses into reproducible RL environments — versioned and shareable.

2

Prime-RL Training

Train across on-demand or reserved clusters, from H200 to B300 — without writing any infrastructure glue.

3

Sandboxed Rollouts

Every rollout runs isolated, so agents can execute code, browse, and call tools safely at scale.

4

Verifiable Rewards

Score outcomes against real signals — tests passing, builds compiling, diffs applying cleanly.

READY?

Your model should get smarter while you sleep.

Operate your own AI lab.

© 2026 Pacer Intelligence Inc. · Built in SAN FRANCISCO

System status · OperationaL

System status · OperationaL

v 2026.5

v 2026.5