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AI @ Scale

Supporting the whole team

Once in place, the Citrine Platform facilitates the work of product developers, data managers, data scientists, and executives.

Collaboration diagram for stakeholders in a materials company

  • Executives can:

    • Evaluate current product portfolio performance across multiple performance dimensions
    • Quantitatively assess risk-reward tradeoffs across their product development portfolio

    design space visualization for materials on two substrates

  • Product developers and materials engineers can:

    Product developers can video

    • Define target performance specifications
    • Encode their domain knowledge to improve AI-model performance
    • Use Sequential Learning to replace traditional design of experiments to determine which candidate materials to test next
    • Dramatically reduce the number of experimental iterations required to find high-performance materials

     

    Artificial intelligence material candidate suggestions

  • Data scientists can:

    Data scientists can video

    • Train, validate, and test AI models
    • Design graphical AI models
    • Perform feature selection and assess model uncertainty

     

    Graphical AI model

  • Data managers can:

    Data managers can video

    • Upload, structure, and link data files from each step of the materials process history
    • Examine, filter, and edit data
    • View data in graphical materials process histories or structured tables
    • Provide guidelines to promote consistency across an organization

     

    Materials process history diagram in the Citrine Platform

Leveraging all your resources

The Citrine Platform supports large scale deployments across international enterprises. Citrine’s modular approach enables  teams across the globe to benefit from each other’s data, domain knowledge, and machine-learning models.

Reuse of digital assets in AI for Materials

Learn how Citrine helps customers scale up their use of AI