The Agentic OS for Physical AI
Any robot. Any task. One Agentic OS.
The entire robotic lifecycle in one stack.
Tested by Robotics Engineers in
Product
A single Python SDK to train, simulate, and deploy general purpose robots.
pip install telekinesis-ai250+ models for perception, planning, manipulation, control, and learning, to build any application across manufacturing, logistics, and more.
Test and refine your application in NVIDIA Isaac Sim, MuJoCo, and other simulators before running it on real hardware.
Take the same application from simulation to any robot, across arms, humanoids, and mobile bases, without a rewrite.
Physical AI Agents
Our Physical AI agent turns natural language prompts into robot motion:
readable and auditable Python code you can review and run on real hardware.
Skills
Classical robotics, foundation models, and reinforcement learning, unified in one OS to help engineers build, deploy, and scale intelligent robots faster.
One program, retargeted across arms, humanoids, and mobile bases.
Learned manipulation policies driving bimanual, contact-rich tasks.
Policies trained in simulation and carried onto real hardware.
Geometric measurement, segmentation, and registration on raw depth data.
Pixel-accurate masks for parts, obstacles, and scenes, from classical methods to deep learning.
Classical, deep-learning, and open-vocabulary detectors behind one interface.
Filtering, morphology, and geometric transforms, composed under everything else.
Ultra-low-latency pub/sub and client/server messaging, cloud to device.
Photorealistic, perfectly labeled datasets generated with Extreme Domain Randomization.
Applications
Architecture
A full-stack, standardized operating system that turns any robot into an intelligent machine.
Read the Docs
Robotic Arm
Mobile Robot
HumanoidAny Robot, Any Form Factor
Applications
The Agentic OS is designed to handle a variety of tasks with production-grade precision from day one.
Localize and grasp parts from a jumbled, unfixtured bin, then hand off a clean pose downstream.
Route parts by type, size, or defect into the right destination, screw by screw.
Stack cases onto a pallet, or unstack mixed layers off one: pipes, cylinders, and cartons, one item at a time.
Read and classify labels moving past a fixed camera, flagging mismatches before the next station.
Place parts into honeycomb trays, foam, or cartons at the exact orientation the shipment needs.
Why us?
Human-level perception meets production-grade reliability, today.
70%
Operational cost savings
12–18
Months to ROI
10+
Supported hardware OEMs
250+
Skills
99%
Task accuracy
0.01mm
Motion precision
Built for engineers
Telekinesis is designed for both robotic OEMs that build the machine and manufacturing firms where robots are deployed.
Bring the Agentic OS up on your hardware once and every customer inherits the same SDK, the same simulator, and the same fleet console, with your machine already in it. No integration project per account.
Mixed vendors, mixed vintages, one interface. Describe the task, prove it in simulation against the real cell, then roll it across the line: versioned, traced, and reversible on every machine you operate.
How it works
Install the SDK, prompt using natural language, prove the behaviour in simulation, then ship the program to real hardware.
One command installs the SDK, with no separate build step and no vendored dependencies to wrangle.
Describe the task in plain language, and the agent composes it into a typed, auditable program from the skill library.
Pick up the aluminum parts from the angled tray and place them in the box in a grid format
from telekinesis import cornea
from telekinesis.synapse import robot, gripper
# Perceive: segment the target part
mask = cornea.segment_image_using_sam(image, color="red")
pose = estimate_pose_from_mask(mask, intrinsics)
# Act: pick and place by composing Skills
robot.set_cartesian_pose(pose, speed=0.25)
gripper.close(force=50.0)
robot.set_cartesian_pose(place_pose, speed=0.25)
gripper.open()Validate the generated application against NVIDIA Isaac Sim and Isaac Lab before it ever touches hardware.
Point the same application at a real robot: one parameter change, not a rewrite or a re-integration.
Pricing
From community projects to enterprise deployments, we've got you covered.
Community support
Dedicated support and development available.
Start Building
Prompt in. Runnable Python out. Running on real hardware by end of day.