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

# Why Avala

> What makes Avala different from Scale AI, Labelbox, Label Studio, and building your own pipeline

Avala is the complete platform for Physical AI data -- from raw sensor recordings to production-quality training datasets. Instead of stitching together separate tools for visualization, annotation, quality control, and export, Avala handles the full lifecycle in one place.

If you are building autonomous vehicles, robots, or any system that perceives and acts in the physical world, Avala was built for your workflow.

## What Makes Avala Different

<CardGroup cols={3}>
  <Card title="" icon="users-gear">
    <p style={{fontWeight: 600, fontSize: '18px', marginBottom: '4px', marginTop: '8px', color: 'inherit'}}>Embedded Engineers</p>
    <p style={{fontSize: '14px', marginTop: '0px', opacity: 0.6}}>Senior Field Development Engineers from Tesla, Waymo, and top AV programs integrate directly into your team -- joining your Slack, reviewing PRs, and co-designing your data pipeline.</p>
  </Card>

  <Card title="" icon="user-check">
    <p style={{fontWeight: 600, fontSize: '18px', marginBottom: '4px', marginTop: '8px', color: 'inherit'}}>15,000+ Domain Experts</p>
    <p style={{fontSize: '14px', marginTop: '0px', opacity: 0.6}}>Career annotators with 12+ months of specialization on your domain. These are not gig workers -- they build institutional knowledge about your ontology and edge cases over time.</p>
  </Card>

  <Card title="" icon="cube">
    <p style={{fontWeight: 600, fontSize: '18px', marginBottom: '4px', marginTop: '8px', color: 'inherit'}}>3D/4D Native</p>
    <p style={{fontSize: '14px', marginTop: '0px', opacity: 0.6}}>Built from the ground up for point clouds, LiDAR, MCAP/ROS, and Gaussian Splats. Not a 2D tool with 3D bolted on.</p>
  </Card>

  <Card title="" icon="link">
    <p style={{fontWeight: 600, fontSize: '18px', marginBottom: '4px', marginTop: '8px', color: 'inherit'}}>Unified Traceability</p>
    <p style={{fontSize: '14px', marginTop: '0px', opacity: 0.6}}>Trace any model prediction back through the export, annotation task, QA review, and source dataset item that produced it. See the [Traceability](/docs/traceability) page for details.</p>
  </Card>

  <Card title="" icon="chart-line">
    <p style={{fontWeight: 600, fontSize: '18px', marginBottom: '4px', marginTop: '8px', color: 'inherit'}}>5x More Data</p>
    <p style={{fontSize: '14px', marginTop: '0px', opacity: 0.6}}>Vertically integrated operations -- tooling, workforce, and QA under one roof -- deliver 5x more real-world training data for the same budget compared to outsourced labeling.</p>
  </Card>

  <Card title="" icon="bolt">
    <p style={{fontWeight: 600, fontSize: '18px', marginBottom: '4px', marginTop: '8px', color: 'inherit'}}>Fast Iteration</p>
    <p style={{fontSize: '14px', marginTop: '0px', opacity: 0.6}}>Go from raw sensor data to pilot datasets in weeks, not quarters. No lengthy procurement, scoping calls, or multi-month onboarding.</p>
  </Card>
</CardGroup>

## How Avala Compares

The table below compares Avala against the most common alternatives for Physical AI data workflows.

| Dimension                    |               Avala               |         Scale AI        |       Labelbox      |       Label Studio      |
| ---------------------------- | :-------------------------------: | :---------------------: | :-----------------: | :---------------------: |
| **3D / LiDAR annotation**    | Native cuboids, BEV, multi-sensor |        Supported        |   Add-on, limited   |      Not supported      |
| **MCAP / ROS support**       |   Native import, viz, annotation  |         Limited         |    Not supported    |      Not supported      |
| **Gaussian Splat**           |     WebGPU viewer + annotation    |      Not supported      |    Not supported    |      Not supported      |
| **GPU-accelerated viz**      |    WebGPU, 6 point cloud modes    |           None          |         None        |           None          |
| **Workforce model**          |   15,000+ career domain experts   |      Gig workforce      |   Partner network   |           DIY           |
| **Embedded engineers**       |    FDEs in your Slack and repos   |      Not available      |    Not available    |      Not available      |
| **Traceability**             |     End-to-end lineage via API    |         Partial         |       Partial       |          Manual         |
| **MCP server**               |      Claude, Cursor, VS Code      |      Not available      |    Not available    |      Not available      |
| **Python + TypeScript SDKs** |         Both, fully typed         |       Python only       | Python + limited JS |       Python only       |
| **Setup time**               |              Minutes              |        Days-weeks       |        Hours        |   Hours (self-hosted)   |
| **Pricing**                  |      Transparent, usage-based     | Custom quotes, minimums | Sales call required | Free (OSS) / Enterprise |

<Tip>
  For a deeper feature-by-feature breakdown including Rerun, Foxglove, and CVAT, see the full [comparison page](/docs/resources/comparison).
</Tip>

## Enterprise Security and Compliance

Avala is built for teams that handle sensitive, pre-release sensor data.

| Standard      | Status                                  |
| ------------- | --------------------------------------- |
| **SOC 2**     | Certified                               |
| **GDPR**      | Data processing agreements available    |
| **ISO 27001** | In progress                             |
| **TISAX**     | Available for automotive customers      |
| **HIPAA**     | Available with BAA for enterprise plans |

All data is encrypted in transit (TLS 1.2+) and at rest (AES-256). Bring Your Own Storage (BYOS) keeps source data in your cloud account -- Avala reads it directly without making copies. See [Security and Compliance](/docs/resources/security-compliance) for full details.

## Get Started

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  <Card title="" icon="rocket" href="/docs/getting-started/quickstart">
    <p style={{fontWeight: 600, fontSize: '18px', marginBottom: '4px', marginTop: '8px', color: 'inherit'}}>Quickstart</p>
    <p style={{fontSize: '14px', marginTop: '0px', opacity: 0.6}}>Create your first dataset and annotation project in under 60 seconds.</p>
  </Card>

  <Card title="" icon="phone" href="mailto:sales@avala.ai">
    <p style={{fontWeight: 600, fontSize: '18px', marginBottom: '4px', marginTop: '8px', color: 'inherit'}}>Talk to Us</p>
    <p style={{fontSize: '14px', marginTop: '0px', opacity: 0.6}}>Contact our team to discuss embedded engineers, managed labeling, or enterprise deployment.</p>
  </Card>
</CardGroup>