> ## Documentation Index
> Fetch the complete documentation index at: https://docs.cadenzalabs.xyz/llms.txt
> Use this file to discover all available pages before exploring further.

# Introduction

> The infrastructure layer for building, simulating, and fine-tuning physical-AI policies.

**Cadenza Labs** builds the software infrastructure that turns a robot into a
learning machine. We give physical-AI teams one stack to **scaffold** a robotics
project, **simulate** it at scale, **fine-tune** a vision-language-action (VLA)
policy on the rollouts, and **deploy** the result to real hardware — without
stitching together a dozen disconnected tools.

If you are training robots, you spend most of your time on plumbing: a simulator
here, a data pipeline there, a training loop somewhere else, and a fragile bridge
to the robot at the end. Cadenza collapses that into a single, coherent workflow.

## What we do

<CardGroup cols={2}>
  <Card title="Simulate physical AI" icon="cube">
    A MuJoCo-based physics core with batteries-included robots, scenes, and a
    reusable action library — so you can roll out missions in seconds, not weeks.
  </Card>

  <Card title="Generate training data" icon="database">
    Every simulated mission is logged tick-by-tick and scored, producing clean
    rollouts ready to become fine-tuning data.
  </Card>

  <Card title="Fine-tune policies" icon="brain">
    Turn rollouts into VLA training sets and LoRA adapters with one command —
    reinforcement learning and supervised fine-tuning, without the boilerplate.
  </Card>

  <Card title="Deploy to hardware" icon="microchip">
    Take the same policy from sim to a physical Go1 or G1 over DDS, SSH, or a
    bridge — the loop you tested is the loop that ships.
  </Card>
</CardGroup>

## How the pieces fit

Cadenza is one stack with two layers. The **SDK is the foundation** — the physics,
robots, and inference core you build on. The **CLI is the workflow on top** — it
takes what you build and turns it into data, training, and deployments.

* **[Cadenza SDK](/sdk/introduction)** — the `cadenza-lab` Python library: the
  MuJoCo-based simulator, robots, action library, and inference stack. This is
  where you **build** — define scenes, drive a Gym loop, or plug in your own
  world model.
* **[Cadenza CLI](/cli-setup/introduction)** — the `cadenza` binary built on the
  SDK. This is where you **operate** — scaffold projects, gather rollout data,
  fine-tune policies, and deploy to hardware, from the command line or CI.

<Note>
  New here? Start with [What we provide](/labs/what-we-provide) for the big
  picture, then build your first robot in the [SDK quickstart](/sdk/quickstart).
</Note>