The ultimate toolchain for robot simulation, synthetic data generation, and model fine-tuning. Build physical AI faster, safer, and with perfect ground truth.
Adopt a "Shift-Testing-Left" paradigm. Catch edge cases in software before deploying to hardware.
Reconstruct complex warehouses and dynamic construction sites using our high-fidelity 3D digital twins. Test your autonomous systems in thousands of edge-case scenarios simultaneously, governed by real-world physics.
Overcome the data bottleneck. Automatically generate perfectly annotated, photo-realistic datasets for object detection, segmentation, and depth estimation. Train your vision models without the manual labeling hassle.
Seamlessly feed real and synthetic data into the PhyCyber foundation models. Use our intuitive UI to orchestrate distributed training jobs, evaluate metrics, and package the model for over-the-air (OTA) deployment.
Built for developers by developers. Integrate simulation natively into your CI/CD pipelines.
from phycyber import Studio, Environment
# Initialize a cloud-based warehouse simulation
env = Environment.load('logistics-hub-alpha')
studio = Studio(env)
# Run randomized trials
results = studio.run_parallel_tests(
agent_policy='latest_checkpoint.pth',
num_trials=10000,
weather_conditions=['clear', 'dusty']
)
if results.collision_rate > 0:
studio.flag_for_retraining()
Join the early access program for PhyCyber Studio and supercharge your robotics team.