Our AI-based approach is designed to use machine learning to identify patterns, and predict material structure properties.

This approach has the potential to digitally target specific material attributes such as weight reduction, wear resistance, corrosion resistance and high-temperature capability.

To date, most advancements in materials have been achieved through trial and error. With our AI-based approach we aim to dramatically reduce R&D time and cost.


AI-powered material acceleration built on real-world data.

Our advantage comes from combining three key factors:

Data mining capability that can generate massive multidimensional materials datasets.

Artificial intelligence and machine learning identifies patterns and predicts the properties of materials based on composition and atomic structure.

Potential proprietary materials and manufacturing processes can be identified, developed and optimized for manufacturing at scale.

Target properties: 

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