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Overview
Citrine Informatics applies machine learning to materials and chemicals development, recommending which formulations to try next. Founded in 2013 in California by Stanford materials scientists, its platform works well with the small, expensive datasets typical of materials research. Manufacturers use it to shorten development cycles for polymers, alloys and coatings.
News
Preparing Your Product Development Team for AI: Three Mindset Shifts That Matter
Materials and chemicals product-development teams are being asked to reach demanding property targets while managing cost, supply risk, regulatory pressure, and limited lab capacity. Many leaders see AI as part of the answer. Yet some programs spend month
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Report
Building Resilience with AI-Enabled R&D: How Stepan Responds Faster to Supply and Market Disruption
About the Webinar Recorded: Thu, 8/27/26 Supply disruptions, raw material price volatility and regional differences in material availability are placing increasing pressure on chemical companies to reformulate products quickly without compromising perform
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Citrine Informatics: Chemical & Materials Development Platform
Today the Citrine Platform regularly powers data-driven materials discovery across industries, having moved beyond one-off demonstrations into routine industrial practice. Getting there required solving a core set of recurring obstacles: experimental data
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Practical AI for Plastics Innovation: Lessons from R&D Leaders
About the Webinar Recorded: Thu, 7/30/26 AI is moving quickly from executive priority to day-to-day product development reality. For plastics companies, the question is no longer whether AI has potential. It is how R&D teams can implement it in practical
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Smoothing the path to AI adoption
About the Webinar Recorded: Tue, 7/14/26 Materials and chemicals teams have plenty of AI ambition. What they do not have is time. Together, Citrine's new capabilities, Apex and Catalyst, help materials and chemicals teams move from product goals to better
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