Train autonomous robots faster. Kite brings simulation, models, agents, data, and cloud compute together in one workspace — URDFs, frontier VLAs, World Labs world generation, SAM 3D objects, MuJoCo + Kimodo physics, and GPU training on demand.

AppSignal — Full-stack monitoring for errors, metrics, and logs

Full-stack monitoring for errors, metrics, and logs

The IDE for autonomous robots. Kite brings simulation, models, agents, and real hardware together in one workspace, so you can ship policies without stitching the stack yourself. Key features: Built around your hardware: Kite handles packages, libraries, and sim-to-real compatibility upfront, so your robot is ready on day one. Frontier models, built in: Physical Intelligence, World Labs, NVIDIA, and Google models are ready to train, alongside Kite's own robotics coding agent. Compute on demand: Cloud GPUs and CPUs that scale to your training run. No local rig to build or maintain. What makes it different from using Cursor/Claude in robotics: Claude does not have all awareness of your sim environment, it takes you time to create a simulator that is realistic and has all you need to build real We have grown and are supporting many researchers building with Kite ML.

How do you handle experiment tracking and reproducibility when worlds are being generated and randomized?

AppSignal — Full-stack monitoring for errors, metrics, and logs

Full-stack monitoring for errors, metrics, and logs

How do you handle experiment tracking and reproducibility when worlds are being generated and randomized?

Kite ML

IDE for Robotics

IDE for Robotics