Bringing predictive power to digital twins

In a decentralised energy world, where predictive maintenance is one critical success factor, the ‘Finite element’ analysis helps predict the behavior of products affected by many physical effects, including mechanical stress, mechanical vibration, fatigue, motion, heat transfer, fluid flow and electrostatics. Even though ‘Digital Twin’ concepts are nothing new, most of these digital twins on the market today lack the capability of modeling large-scale assets in great level of detail. Therefore, these models cannot be utilised for understanding structural conditions and enabling predictive analytics, and they lack the speed for use in real-time applications. The Akselos’s patented algorithms and technology has the power to model and simulate the behavior of (critical) infrastructure, allowing better designs, lifetime extension and optimized operations & maintenance to reduce CAPEX and OPEX.
  • Founding date


  • Country


  • Funding Round

    Series B

  • Management Team

    CEO - Thomas Leurent
    CTO - David Knezevic
    VP of Engineering - Phuong Huynh
    Senior VP - John Bell

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