Data Engine
Synthetic Data
The Data Engine provides the data infrastructure for Physical AI training: standardized datatypes that act as fixed contracts between Skills and Agents, and photorealistic synthetic datasets generated with Extreme Domain Randomization (EDR) for sim-to-real transfer. Pick the group below that matches what you're looking for.
Data Types
Every Skill and Agent input/output is grounded in a standardized datatype - point clouds, bounding boxes, images, meshes, vectors, matrices, and annotations - so components can be composed and reused without ad-hoc data wrangling.
Synthetic Datasets
Telekinesis publishes photorealistic synthetic datasets for training and evaluating computer vision and robotic manipulation models - pixel-perfect annotations, no manual labeling, generated with Extreme Domain Randomization (EDR) to close the sim-to-real gap. All datasets are free on Kaggle.
Where to Go Next?
Ready to go deeper? Browse the Telekinesis Skill Examples repository for a runnable example covering every Skill.
Skill Examples
One runnable example per Skill, across vision, 3D, hardware, and robotics.
Explore →Explore the Docs
Skills
Vision, 3D, hardware, and robotics skills — the full API reference.
Explore →Agents
Turn natural-language instructions into robot code with Tzara, the VS Code agent.
Explore →Data Engine
Generate and manage synthetic datasets for training Physical AI models.
Explore →BabyROS
Lightweight pub/sub and service primitives for building robot communication layers.
Explore →Applications
Real-world use cases: pick-and-place, palletizing, quality inspection, and more.
Explore →