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

# Connect

> Integrate your growth and characterization data with Atomscale

The first step to using Atomscale is connecting your data sources. When data arrives, Atomscale's adapter models automatically process it into structured, analysis-ready representations.

This page covers the most common connection methods and walks you through your first integration.

## Connection Methods

Atomscale supports multiple ways to bring data into the platform, from zero-setup screen capture to fully automated programmatic integration:

<Tabs>
  <Tab title="File Upload">
    Upload characterization data or process log files manually.

    **Best for**: Initial evaluation, ad-hoc usage, historical data

    **Requires**: Accessible data files in a supported format
  </Tab>

  <Tab title="Screen Capture">
    Stream data by capturing the screen of a workstation or instrument GUI.

    **Best for**: Zero-setup live streaming, instruments without accessible data files, getting started with real-time analysis quickly

    **Requires**: Access to the GUI window to capture from
  </Tab>

  <Tab title="File Watcher">
    Use the Atomscale desktop agent to automatically upload files in a local directory.

    **Best for**: Set-and-forget automated upload where files are already being written to disk

    **Requires**: Atomscale desktop agent, API key
  </Tab>

  <Tab title="Programmatic Integration">
    Upload files or stream data programmatically using the <Link href="/sdk">Python SDK</Link>.

    **Best for**: Automated 24/7 real-time data analysis, high-volume upload, custom integration with existing infrastructure

    **Requires**: SDK setup in a Python application, API key, stable network connectivity
  </Tab>
</Tabs>

## Your First Connection

Choose the path that best fits your situation:

### Option A: Upload a File

The quickest way to get data into Atomscale, useful for initial evaluation or loading historical data.

<Steps>
  <Step title="Access Web Upload">
    In the Atomscale dashboard, click <Badge stroke color="blue">Add Data</Badge>
    in the sidebar and select <Badge stroke color="blue">Upload</Badge>
    from the connection options.
  </Step>

  <Step title="Upload Files">
    **Drag and drop** your characterization data or process log files, or **click to browse**.
    Atomscale auto-detects most common instrument file formats.
  </Step>

  <Step title="Confirm and Upload">
    Click <Badge stroke color="blue">Upload</Badge>
    to start uploading files in the background. The platform will notify you when uploads complete
    and processing is ready.
  </Step>
</Steps>

### Option B: Stream via Screen Capture

The quickest way to get live data flowing, with no agent install or API setup required.

<Steps>
  <Step title="Open Screen Capture">
    In the Atomscale dashboard, click <Badge stroke color="blue">Add Data</Badge>
    in the sidebar and select<Badge stroke color="blue">Screen Capture</Badge>.
  </Step>

  <Step title="Select a Window">
    Choose the instrument GUI or application window to capture from. Atomscale streams the visual
    content and extracts quantitative data in real-time.
  </Step>

  <Step title="Verify Data Extraction">
    Confirm that Atomscale is extracting the expected data from the captured window. Derived metrics
    should begin appearing within seconds.
  </Step>
</Steps>

<Tip>
  Screen Capture is particularly useful for instruments where the data isn't easily accessible as
  files or API streams, such as RHEED camera feeds or proprietary instrument GUIs.
</Tip>

### Going Further

Once you've verified that Atomscale processes your data correctly, consider setting up persistent connections for ongoing use:

* **File Watcher**: Install the desktop agent to automatically upload files from a monitored directory. In the dashboard, click **Add Data** → **File Watcher** to download the agent and configure a watched directory.
* **Python SDK**: For full programmatic control, see the [SDK documentation](/sdk) to set up automated streaming or bulk upload pipelines.

## Supported Instruments

Atomscale includes built-in adapters for common characterization and process data across thin film growth:

| Category     | Instruments                                         |
| ------------ | --------------------------------------------------- |
| Diffraction  | RHEED (STAIB, kSA, custom), XRD, LEED               |
| Spectroscopy | XPS (PHI, Kratos, Thermo), Raman, Ellipsometry, NMR |
| Microscopy   | SEM, AFM, TEM, STEM                                 |
| Process Logs | MBE, MOCVD, CVD, ALD, PVD, and sputtering systems   |
| General      | CSV, HDF5, IMM, TIFF, VMS, and other common formats |

<Note>
  Don't see your instrument or file format? Contact our team at
  [support@atomscale.ai](mailto:support@atomscale.ai) to quickly set up a new integration.
</Note>

## Data Organization

As you connect data, Atomscale organizes it around a few core concepts that carry through to analysis and monitoring:

* **Data Items** are individual files or data streams: a single RHEED recording, an XPS
  spectrum, or a process log.
* **Physical Samples** group data items associated with a sample. A physical
  sample might have in-situ RHEED data, ex-situ XPS,
  and the growth process log, all linked together.
* **Projects** group related physical samples by growth system, research campaign, product
  line, or however fits your workflow. Projects are used for run-to-run analysis and monitoring.

## Explore Your Data

Once data is connected, the **Data Catalog** is where you
find it all. Click <Badge stroke color="blue">Data</Badge> in the sidebar to
open a table of all your
data items, where you can search, sort, and filter across all fields and metadata types.

## Next Steps

With data connected, Atomscale's adapters extract derived metrics like lattice spacing, intensity profiles, and composition signatures, depending on your data type. You're ready to start comparing runs, monitoring growths, and exploring your process data.

<CardGroup cols={2}>
  <Card title="Analyze Your Data" icon="chart-mixed" href="/platform/get-started/analyze">
    Compare runs, track active growths, and extract process insights from your data.
  </Card>

  <Card title="Connection Reference" icon="book" href="/platform/reference/connecting-data/manual-upload">
    Full list of supported formats, advanced configuration, and troubleshooting.
  </Card>
</CardGroup>