Giovanni Degiorgi is a forward-thinking Solution Architect at Swiss Post, based in Lugano, Switzerland. With a strong focus on digital transformation and cloud adoption, he plays a key role in guiding Swiss Post’s transition toward scalable, secure, and data-driven solutions. His expertise in cloud architecture and machine learning systems has been instrumental in driving innovation and operational efficiency across the organization.
Giovanni recently earned a Master’s degree in Machine Learning and Artificial Intelligence from SUPSI (University of Applied Sciences and Arts of Southern Switzerland), which deepened his technical foundation and strengthened his ability to bridge traditional IT infrastructure with modern AI-driven architectures.
In his current role, he supports development teams in defining foundational blueprints for cloud and MLOps practices on AWS—streamlining the deployment, monitoring, and lifecycle management of machine learning models in production.
Moving a machine learning model from exploration into production is never a straight path.
Academic success often relies on clean datasets, controlled environments, and benchmark metrics—but in the real world, models face data drift, latency constraints, integration challenges, and the risk of wrong predictions directly impacting customers and business processes.
In this talk, we share our journey of bringing fraud detection models from research into production at Swiss Post. We highlight the role of the shadow model approach, where new models run in parallel with production systems to safely validate performance on live traffic.
You’ll learn how shadow testing helps measure robustness, monitor data drift, and align with business KPIs—without introducing operational risk.
Attendees will take away concrete practices for bridging the gap between academic experimentation and real-world operations: how to design safe rollouts, build monitoring pipelines, and decide when a model is ready for prime time.
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