Quastify Materials offers an AI-driven platform that integrates quantum mechanics with machine learning to create digital twin technology for optimizing chemicals and materials. This approach significantly reduces research and development time and costs, facilitating faster market entry for new materials.
Funding
Funding not disclosed
Founders
Product
Problem
Developing new chemicals and materials is a costly and time-intensive process, often requiring millions of dollars and several years to bring a single material to market. Traditional methods rely on extensive experimentation and data collection, with a high failure rate before a viable material is discovered.
Solution
Quastify Materials offers the ΦAI platform, which leverages physics-based AI to create digital twins for chemical manufacturing. By integrating quantum mechanics with machine learning, the platform predicts molecular properties *in silico*, significantly reducing the need for physical experimentation. This approach compresses computational time from millions of hours to just one, enabling companies to explore a wider chemical space and identify promising materials faster and at a fraction of the cost. The platform generates confidential computational data ("Bricks") that predict the properties of large molecules and materials, while safeguarding proprietary information.
Target Audience
Quastify Materials targets companies in the chemical, pharmaceutical, and materials industries seeking to accelerate their R&D process and reduce the costs associated with new material development.
Features
- Physics-based AI models that work with limited data to predict material properties
- AI models applicable across all areas of chemistry
- Continuous model improvement with every new customer
- Scalable computational data assets for chemical manufacturing
- Ability to predict molecular properties *in silico* before lab synthesis
- Reduced computational costs compared to traditional methods