CuspAI Launches ‘AI Materials Foundry’ a Global Network to Accelerate Breakthrough Discoveries

CuspAI announced the launch of the AI Materials Foundry, bringing together a global network of data, labs, compute and scientific expertise for the design of new materials, orchestrated by a single agentic platform.

Over 45 organizations join as founding members, including NVIDIA, who will provide the compute infrastructure, and Meta’s Fundamental AI Research Team, who develop the Universal Model for Atoms (UMA), a frontier atomistic chemistry model for materials science.

CuspAI’s proprietary AI platform, MIRA, sits at the heart of the network, enabling partners to run full discovery cycles – from generative materials design through simulation, synthesis route planning, and coordinated experimental validation. The platform is underpinned by the largest curated experimental materials datasets in the world.

The collaboration seeks to end the materials bottleneck constraining progress. Semiconductors, clean energy and advanced manufacturing are among the industries facing the same challenge: while the engineering needed for innovation is well understood, the constraint is materials.

“If we don’t make progress fast, the next 50 years of industrial progress will be constrained by a single challenge: the world needs materials that don’t yet exist. That’s what we’re on a mission to solve - combining frontier agentic AI with deep domain expertise, exclusive data access and close customer partnerships. We’re delighted to be joined by more than 45 leaders in their fields to advance materials discovery.”

– Dr Chad Edwards, CEO and Co-Founder, CuspAI

"As AI transforms the physical world, new materials will open up new frontiers across semiconductors, energy and advanced manufacturing. The AI Materials Foundry brings NVIDIA accelerated computing infrastructure together with world-class chemistry and materials expertise to help power the next generation of materials discovery.”

– Ian Buck, Vice President of Hyperscale and HPC, NVIDIA

"We're proud to be longstanding partners with CuspAI and now as founding members of the AI Materials Foundry ecosystem. Our open source frontier models for materials science research will enable more teams to tackle previously intractable challenges, more precisely and more quickly than before."

– Rob Fergus, Vice President, AI Research and Head of FAIR, Meta

Unlocking AI-powered materials discovery

Software-led materials discovery requires four things: high quality training data at scale, to make AI predictions reliable; compute powerful enough to screen at molecular resolution across billions of candidates; synthesis infrastructure to move from digital design to physical reality; and domain expertise to interpret what the machine finds and know what to do with it.

CuspAI’s AI Materials Foundry assembles all four, for the first time, providing the production infrastructure for industrial materials discovery. Rather than relying on the physical constraints of a single, isolated laboratory, CuspAI’s ecosystem approach creates a compounding intelligence loop: breakthroughs achieved within the network have potential to accelerate discovery timelines across the entire global value chain.

CuspAI brings a track record for accelerating discovery. With a single customer, Finnish chemicals company Kemira, CuspAI was able to screen a search space of 300 trillion potential molecular structures, delivering twenty validated novel candidates for further testing and validation. This process previously took the customer years, while CuspAI’s programme was achieved in six months.

One Foundry project already underway is a new multi-year partnership between CuspAI and the Agency for Science, Technology and Research (A*STAR), Singapore’s lead public sector R&D agency. The collaboration will combine AI-driven discovery with autonomous synthesis capability across semiconductors, carbon capture and advanced electronics.

Private, protected, partner-led agentic design

Through the Foundry programme, members will get to learn about state of the art methods in AI for Science and agentic materials discovery, including how to deploy CuspAI's discovery platform and autonomous scientific agent, MIRA, within their existing R&D infrastructure.

A partner defines what they need: a compound with specific thermal stability, a semiconductor with a target bandgap, a catalyst with a defined reaction profile, a polymer meeting a set cost threshold – and MIRA generates candidate structures using generative models trained on the world's most comprehensive experimental dataset. Capable of running property prediction at scale across millions of candidates, MIRA selects the most promising, designs synthesis routes matched to the available lab infrastructure in the network, and routes the work to the right facility based on capability, geography and throughput. It tracks outcomes, feeds results back into the model, and sharpens its predictions with every cycle.

Partner data is protected in private Foundry instances. The platform is designed for industrial confidentiality at the scale of multinational and government operations.

At the simulation layer, the Foundry runs on kUPS: an open source molecular simulation toolkit built by CuspAI in collaboration with the NVIDIA ALCHEMI (AI Lab for Chemistry and Materials Innovation) team and will leverage Meta’s UMA, which enables fast, accurate simulation of atomic interactions across the periodic table. kUPS is integrating with ALCHEMI, enabling a continuous pipeline from candidate generation to physical property prediction at GPU scale.

CuspAI’s team, and scientific architecture, were built to solve the material discovery problem. CuspAI CTO and co-founder, Professor Max Welling, co-invented the variational autoencoder (VAE) and the equivariant neural network architectures that now underpin generative molecular design. Chief Scientific Officer, Professor Aron Walsh FRS, is one of the world's foremost computational materials scientists. John Giannandrea, who built and led AI research at Google before serving as Apple's SVP of Machine Learning and AI Strategy, will help set up US foundry operations.

The quality of any AI system for materials discovery is determined almost entirely by the calibre of the data it was trained on. CuspAI has secured exclusive AI training rights to the datasets that make up the foundational experimental records of materials science including the Cambridge Structural Database via CCDC and the Inorganic Crystal Structure Database via FIZ Karlsruhe. It also has licensed access to materials science content from Wiley and other leading publishers of scientific journals. This dataset is paired with frontier atomistic chemistry models from Meta and compounded by every validated experimental result returned through Foundry programmes, ensuring the data advantage widens with each programme completed.

FOUNDING PARTNERS

• 3M
• AMD
• Applied Materials
• ASMPT
• Caelux
• Fujifilm
• The Goodyear Tire & Rubber Company
• Henkel
• Hitachi High-Tech
• Hyundai Motor Group
• Johnson Matthey
• JSR Corporation
• Kemira
• Kioxia
• Lam Research
• LG CNS
• Merck
• Meta
• Mitsui Chemicals
• NVIDIA
• Oxford PV
• Qnity Electronics, Inc
• Resonac
• Samsung
• Shimadzu
• SoftBank Corp.
• Tokyo Electron (TEL)
• Topsoe
• Umicore
• Universal Display Corporation (UDC)
• VisionPower Semiconductor Manufacturing Company

LAB NETWORK

• A*STAR
• AMOLF
• ATLANT 3D
• Avantium
• Big Chemistry
• Cambridge University
• Dutch Institute for Fundamental Energy Research (DIFFER)
• Eindhoven University of Technology
• Henry Royce Institute
• hte - the high throughput experimentation company
• IMEC
• Technical University of Denmark (DTU)
• Tyndall National Institute
• University of Amsterdam
• VSParticle

DATA PARTNERS

• CCDC
• ICSD and FIZ Karlsruhe
• Wiley

CuspAI | www.cusp.ai