Fast Computing
Real-time computing solutions for product and process development.
| Date | Investors | Amount | Round |
|---|---|---|---|
N/A | Spinout | ||
| Total Funding | 000k | ||
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Fast Computing is a startup of the International School for Advanced Studies (SISSA) in Trieste, Italy, that provides real-time computing and data analytics solutions. Founded in 2022 as a spin-off from the SISSA mathLab research group directed by Prof. Gianluigi Rozza, the company aims to accelerate innovation and reduce computational time and costs for industries. The executive team includes Andrea Martini as CEO, Nicola Demo as CTO, and Gianluigi Rozza as the scientific director.
The company's core technology is based on reduced order models (ROMs), which create computationally inexpensive yet accurate and reliable simulations. This technology was developed through a €1.6 million grant from the European Research Council (ERC) for the AROMA-CFD project and later tested with industrial cases via an ERC Proof of Concept grant for the ARGOS web platform. Fast Computing integrates ROMs with artificial intelligence, machine learning, high-performance computing (HPC), and data science to deliver its services. The firm's offerings include the development of digital twins for predictive maintenance, image recognition, and uncertainty quantification, catering to clients across various sectors by enabling faster research and development cycles. A key value proposition is the significant reduction in simulation times, for instance, cutting a 5-minute simulation down to 0.1 seconds.
As a benefit corporation, Fast Computing is committed to creating a positive impact on the community, the environment, and its stakeholders, aiming to bridge the gap between academic research and industrial application.
Keywords: reduced order models, real-time simulation, computational reduction, data analytics, predictive maintenance, digital twin, high-performance computing, scientific computing, mathematical modeling, SISSA mathLab, AROMA-CFD, ARGOS platform, machine learning, industrial simulation, computational fluid dynamics, engineering simulation, process optimization, product development, applied mathematics, technology transfer