Azymov

The Problem

Training a humanoid robot today requires configuring hardware, setting up GPU clusters, coding in simulation tools like Isaac Sim or MuJoCo, collecting real-world demonstrations through teleoperation, preprocessing data, training ML models on private infrastructure, and repeatedly debugging sim-to-real failures. This loop takes weeks or months per task and requires a multi-disciplinary team to manage simulation, machine learning, data annotation, and hardware integration.

The Solution

Azymov makes robot training fast, intuitive, and fully integrated—entirely in your browser. Open the web app, type "create a cluttered kitchen for a humanoid to pick up dishes," and our World Agent AI instantly builds a realistic 3D environment with physics, lighting, and affordances. Drag in a Unitree or any humanoid model, add dynamic agents (humans, pets, obstacles), and launch cloud-based reinforcement or imitation learning with a single click.

Live training metrics and replays appear in your browser. When the policy performs well across diverse scenarios, export it directly to your real robot via ROS or custom SDK. Real-world failures? Log them and feed them back into the platform to retrain instantly. What normally takes months now happens in days—no specialized hardware, infrastructure, or large engineering team required.