QuMatrix established
Project-based R&D across quantum, AI, HPC, robotics, and applied computation.
Company
QuGradient is an Applied Quantum AI product company. We commercialize advanced research by translating AI, quantum-inspired computing, advanced computing, and emerging quantum technologies into practical intelligence products.
QuGradient grew out of the QuMatrix ecosystem, bringing a deep foundation in quantum computing, AI, HPC, and applied research into a product company.
Our role is to carry research through applied technology and into software people can use. Each product addresses a specific customer problem while drawing on a shared scientific foundation.
Project-based R&D across quantum, AI, HPC, robotics, and applied computation.
The quantum and AI research foundation behind QuGradient’s products.
An Applied Quantum AI product company working across multiple markets.
Scientific depth.
Experience bringing technology into practice.

Co-Founder, Chief Scientist
Creator of the core quantum and computational libraries behind QuGradient's products. Quantum mechanics, quantum computing, AI/ML, robotics, and performance modeling.

Co-Founder, COO and AI Strategy
Former Chief AI Scientist at S&P Global and CAIO at New York Life. 30+ years at IBM Watson Research, Columbia adjunct, 50+ papers and multiple patents.

Quantum ML Research
PhD Quantum Machine Learning. Leads quantum-AI research and the algorithms that power QuGradient's products.
Senior Advisor
Director of AIM London (Centre for Innovation and Enterprise) and co-director of the KIE/DHT Innovation & Big Data Analytics Lab.
Senior Advisor
30+ years across industry, commerce, and academia in decision modeling, consulting, and education.
Senior Advisor
30+ years in hardware modeling, AI/ML, HPC, quantum computing, finance, and economics.
Our customers should benefit from advanced technology without needing to master it.
Product experiences abstract technical complexity and make the resulting intelligence interpretable.
Classical, quantum-inspired, and hybrid methods help products deliver value as quantum hardware matures.
Match methods to the task, evaluate results, and avoid assuming quantum advantage.
Explore a product, discuss an application,
or connect with the team behind the science.