Artificial intelligence is reshaping the automotive and fleet management sectors, bringing automation and precision to processes that have long relied on manual, inconsistent inspection. Vehicle damage assessment is one of the clearest examples, and it is the focus of the Damage Control project.
Together with TubeIQ and AAA-1 RENT, we combined AI, computer vision, and high-performance computing to build a system that assesses vehicle damage automatically, turning photos, voice notes, and documents into structured, standardized reports. We led the development of the underlying multimodal AI models and HPC workflows, running large-scale experimentation on the LUMI supercomputer to take the solution from research to real-world deployment. Access to LUMI was enabled through the FFplus program, funded by the European High-Performance Computing Joint Undertaking (EuroHPC JU).
The result: 30–40% faster damage-report processing, 20–25% lower inspection costs, and up to 30% fewer disputes between renters and operators — already pointing to a meaningful shift in how fleets can handle damage assessment going forward.
To learn more about the project's results and future outlook, read the full success story on the FFplus website: https://www.ffplus-project.eu/en/success-stories/hpc-enabled-damage-control-for-rental-car-fleets/
