5 Q’s with Juha Riippi, CEO of Quanscient

Engineering teams often face significant bottlenecks when attempting to simulate complex physical systems. Current design tools frequently rely on computing architectures that cannot keep up with the demands of modern semiconductor, aerospace, or energy projects. This reliance on older technology forces companies to build costly physical prototypes rather than iterating through digital models.

Juha Riippi, CEO of Quanscient, is addressing this issue with a cloud-based engineering platform. His approach combines multiphysics simulation with machine learning to model heat, electricity, and fluid flow simultaneously. By running thousands of simulations in parallel, the platform generates the data required to build predictive AI models. This allows engineers to test variables and identify optimal configurations before moving into production.

While the platform currently runs on classical cloud-based infrastructure, the company is preparing for the integration of quantum computing. The goal is to offload the most computationally intensive tasks to quantum hardware, particularly for complex challenges like computational fluid dynamics. Riippi noted that they have already demonstrated the ability to solve small versions of fluid flow equations using quantum processors.

Industries such as semiconductor manufacturing already use this platform to simulate micro-components like accelerometers and gyroscopes. Other applications include the design of electric motors and the modeling of plasma-confining magnets for fusion energy research. As quantum hardware becomes more mature, the team expects these capabilities to expand into broader defense and maritime sectors.

The long-term vision is to create a unified platform where AI, cloud resources, and quantum hardware coexist to solve problems that are currently impossible for standard supercomputers to handle. This shift aims to reduce the time required for research and development while ensuring the creation of more sustainable and efficient products across various technical fields.