Our deep learning algorithms increase your understanding of your data, mitigate the noise, and fill in the gaps in sparse datasets. Our cutting-edge tools use confidence levels to guide where you need to test further and enable efficient error or outlier detection.
We use artificial intelligence to optimize current materials whilst improving key properties and enabling the optimal selection of requirements for new formulation design. Our technology speeds up the time to market and significantly reduces prototype costs, eliminating the need for trial-and-improvement.
Our technology is able to predict failures based on live input, therefore reducing wastage of materials. We help maintain a consistent output in different environments and understand the relationships between process inputs and product outputs, thereby increasing the overall efficiency of the target process.
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