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Atomscale brings process logs and characterization data together so you can monitor growths, investigate unexpected behavior, and keep the evidence behind your decisions.

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Choose a task

Connect Data

Upload files or collect data from instruments with desktop integrations and the Python SDK.

Investigate a Growth

Ask the assistant to build a notebook, inspect the evidence, and refine the analysis.

Monitor Growths

Watch incoming RHEED and tool-state data and review completed sessions.

Use Analysis Notebooks

Find specific instructions for creation, editing, saving, versions, and access.

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How your data fits together

Data items hold individual recordings or measurements. Physical samples bring related data together, and projects group samples for an investigation or campaign. Processing workflows extract results according to the data type; notebooks let you investigate those results alongside your engineering context. If you are new to the platform, follow Get Started. For example investigations, browse the Guides. Case Studies describe specific applications and their results.

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Programmatic access

Use the Python SDK for data access and custom analysis, the API reference for endpoint details, or the MCP server to connect supported assistants to Atomscale.