Technology company MaterialsZone has launched a new product development feature that aims to “make iterative AI models more accessible for faster innovation.”
As consumer demand propels businesses to launch new beauty products faster than ever before, the Israeli company said the feature will “offer greater autonomy in experimentation processes and enhance their ability to align development efforts with R&D timelines.”
We spoke to MaterialsZone’s CPO Ori Yudilevich to find out more about how the AI-guided product development feature works.
CosmeticsDesign-Europe (CDE): Can you tell us more about this innovation please. How does it work? How can it support beauty companies?
Ori Yudilevich (OY): MaterialsZone’s new AI-guided product development feature leverages machine learning to provide targeted recommendations for experiments, significantly shortening the time needed for product development.
By analysing historical data and identifying optimal paths forward, the feature helps beauty companies streamline their R&D processes.
This approach accelerates innovation by focusing efforts on the most promising experiments, reducing trial-and-error, and ultimately enabling faster development of new formulations. Beauty brands can use this tool to bring cutting-edge products to market more quickly while staying ahead of consumer trends and demands.
This approach accelerates innovation by focusing efforts on the most promising experiments, reducing trial-and-error
MaterialsZone CPO Ori Yudilevich
CDE: How could this innovation disrupt/impact the future of the beauty industry?
OY: By focusing on the most promising experiments, it reduces development timelines, minimises costs, and accelerates innovation. Leveraging MaterialsZone’s organized data, this feature guides the R&D process, enabling beauty companies to efficiently develop high-performing products and bring them to market quickly while staying ahead of consumer trends.
CDE: How do you think AI will have changed the cosmetics R&D process five years from now?
OY: In five years' time, AI will likely make the cosmetics R&D process even faster, more cost-effective, and highly personalised.
It will automate routine tasks, enabling researchers to focus on innovation. Virtual experiments and simulations will become standard, dramatically reducing the need for physical testing. AI-driven insights will also make it easier to tailor products to individual consumer needs, further advancing customisation in beauty products.
Additionally, AI will enhance sustainability by optimising the use of materials and minimising waste.
CDE: Do you have any future plans to further update this solution in the future? If so, can you tell us more about it at this stage?
OY: Yes, we are continually working to enhance the platform’s capabilities. Future updates to our AI model will incorporate additional factors such as chemical properties, sustainability, and regulatory requirements, making the models even more effective and further reducing product development timelines.
Our focus remains on driving innovation and supporting the evolving needs of materials-based industries, including cosmetics and beauty.
