Axyon AI – Leveraging HPC for AI and DL-powered solutions for asset management

Presentation of the problem and objective of the experiment

The objectives of the Experiment are:

  • To build a new set of product features and predictive models based on highly innovative deep learning technologies and requiring high computation power, 
  • ​To enhance the current offering of Axyon AI extending its target market especially to small/medium-size customers that need a complete, end-to-end solution,
  • ​To implement solutions to better adapt the models to the rapid changes that often occur in the financial markets.

Short description of the experiment

The Experiment has the overall goal of improving the service offered by Axyon to its clients through several technological advancements. Three main areas of improvement (scalability, risk management and adaptiveness) have been identified and each will be the target of a dedicated task. In particular, during the first part of the Experiment Axyon and Cineca will work on improving the computational scalability of the Axyon ML platform. Then, the focus will be on enhancing Axyon IRIS risk management features for end-to-end portfolio construction. In the last part of the Experiment, with the collaboration of AImageLab, the activities will be focusing on increasing the adaptiveness of Axyon IRIS forecasting models.

Organisations involved:

End user: AXYON AI
HPC Provider: CINECA
Domain Expert: Università degli studi di Modena e Reggio Emilia