About

Lucidity Sciences is a team of mathematicians, engineers, and scientists who believe that meaningful innovation comes from depth, not hype. Our Lumawarp engine brings new life to machine learning by creating custom models that adapt to your data using a robust new mathematical and hardware framework—delivering speed, precision, and reliability that outperforms the leading commercial ML solutions. 

The story of Lucidity Sciences began over a decade ago with mathematician Dr. Richard Wellman. In 2011, Dr. Wellman began exploring a simple question with his research assistant Alexandra Pasi: What if learning machines could learn in a more meaningful way? Once a cornerstone of machine learning, kernel-methods had promised elegant, robust, and uniquely interpretable solutions—but in practice, they struggled with the variability and scale of real-world data. For the next decade, Dr. Wellman pursued this problem, developing a method for novel kernel generation. In essence, he solved the dual problems of scalability and adaptability that had long limited kernel-based approaches.

In 2020, Dr. Pasi rejoined him to scale his proof of concept into a working engine capable of handling diverse real-world data sets. Together they built the foundation for what would become Lumawarp, Lucidity’s core technology—a mathematically grounded and highly-performant alternative to the compute-heavy paradigms that dominate machine learning today.

In late 2024, Dr. Pasi and Dr. Wellman expanded their team to include additional mathematicians, scientists, and experienced commercial architects, founding Lucidity Sciences. Within months, Lucidity’s prototypes were outperforming industry-standard machine learning methods in applied research across medicine and science. In its first year, the company secured its initial round of investor funding and joined NVIDIA’s Inception Program, gaining access to advanced GPU technology to further accelerate development.

Their comprehensive training and inference engine Lumawarp will be broadly commercially available starting in January 2026, with beta testing ongoing. After over a decade of research and development, their mission is clear: 

Deliver breakthrough machine learning technology to the industries that need it most—helping experts achieve faster and more reliable outcomes.