Across industries such as energy, automotive, and semiconductors, the development of new materials holds the key to solving many pressing challenges. While materials informatics—using computers to search for new compounds—has improved efficiency, the process still requires enormous time and computational resources.
Preferred Networks (PFN), together with its group company Matlantis Corporation, applies AI technologies to materials science to dramatically accelerate materials discovery. Through this work, PFN group aims to realize a more sustainable world powered by innovative new materials.
Matlantis™ is a universal atomistic simulator that supports large-scale material discovery by reproducing new materials’ behavior at an atomic level on the computer. Jointly developed by PFN and ENEOS and provided by a joint venture since July 2021, Matlantis has supported over 100 companies and organizations as a cloud-based software-as-a-service for elucidating material properties and discovering various new materials. PFN develops Matlantis's core technology PFP (Preferred Potential), a universal machine learning interatomic potential.
PreferredAI™ is a group of PFN's products and services for solving diverse business challenges across industries.
Talent Scouter: Aptitude assessment through AI avatar interactions, ensuring consistent talent acquisition
Work Suite: AI agent supporting day-to-day operations using company-internal data
Insight Scan: Classification of large text data from reviews and surveys to uncover valuable insights
