Burgeon Studio builds AI native software for life sciences. AI is the default tool for almost everything we do. We add quantum methods only for the specific problems where data complexity outgrows what AI can handle, so you never pay for complexity you do not need.
Burgeon Studio is an AI native software company. AI is the first tool we reach for on any problem that involves language, data or prediction, and it shapes how our products are designed, built and delivered.
Quantum is not a feature we add for show. We bring it in only when a problem’s size and structure, such as the number of options to search or the electronic structure of a large molecule, is more than AI can handle. Even then we test it against AI and classical methods first, and keep it only if it adds real value.
Spherix simulates physics directly, so its engine is classical and mechanistic. It is agent based simulation built on PhysiCell, the open source, peer reviewed cell simulator from the Macklin lab, and it follows every individual cell as it grows, divides, consumes oxygen and dies. It makes no AI or quantum claim about its results. Turn the oxygen dial and watch one cell respond.
For molecular systems with complex electronic structures, variational quantum algorithms on cloud QPUs offer a route to energy estimates where classical methods become costly. A quantum circuit prepares a trial state, a classical optimiser adjusts it, and the loop repeats. We would use this only after AI and classical methods fall short on a specific molecule.
Many valuable decisions in life sciences are combinatorial: selecting the best subset from a large population, or the best configuration from an exponential space of options. AI and classical search handle most of these well. When the number of options grows past what they can search, quantum annealing, reached through a cloud API, becomes a candidate.
Post quantum cryptography does not use quantum computers. It is classical cryptography designed to withstand attacks by future quantum computers. NIST finalised the first standards in 2024, including ML-KEM, ML-DSA and SLH-DSA. We build that migration in from the start.
We do not add quantum where AI already does the job. Our products use AI and classical computation for the great majority of their work, and bring in quantum methods only for the specific problem classes where they add real value. This is not a marketing choice. It keeps your costs down, and it is why you can trust what we tell you.
We are happy to explain where AI does the work, where quantum might be added, and what that means for your work.