Quantum Formatics

About Quantum Formatics

Based in Cambridge, MA, Quantum Formatics is a materials discovery company founded in 2025 that is focused on developing next-generation superconductors. The company's mission is to drastically reduce the time required to discover new superconducting materials, from decades to days, using a proprietary platform that combines artificial intelligence, quantum chemistry, and high-throughput experimentation. This approach targets the creation of materials that can be manufactured efficiently and operate at higher temperatures than current commercial options. The company was co-founded by CEO Jason Gibson, Ph.D., and Patrick Taylor. Gibson's doctoral research in Materials Science and Engineering at the University of Florida became the foundation for the firm's core technology and earned the university's 'Invention of the Year' award. His background includes a fellowship in Applied Machine Learning at Los Alamos National Laboratory and recognition in Forbes' 30 Under 30 for his work at the intersection of AI and advanced materials. Quantum Formatics operates a hybrid model, integrating its AI-driven discovery platform with a physical lab for rapid experimental verification. The platform generates a large database of candidate materials and screens them for critical properties like stability, manufacturability, and superconducting performance. The most promising candidates are then synthesized and tested in-house. The company's business model appears to involve the in-house discovery and eventual production of new superconducting wires, aiming to outperform existing market incumbents. Its target markets include high-field applications such as scalable fusion energy, lossless power transmission, and more accessible MRI machines. By improving magnetic confinement efficiency in fusion reactors and lowering the cost of MRI machines, the technology addresses multi-billion dollar markets. Quantum Formatics is backed by investors including The Engine (an incubator from MIT), MIT.nano, and the US National Science Foundation (NSF). The company received a $305,000 SBIR Phase I award from the NSF for its AI-accelerated discovery workflow. With institutional backing, the firm has built a purpose-built, private AI cluster with infrastructure partners like Lenovo to handle diverse workloads, including machine learning, quantum mechanical simulations, and inference without the constraints of variable cloud costs.