04.09.2026 –, Workshop Room - CZ 107
This workshop provides a hands-on introduction to building AI-enhanced applications using a
combination of large language models, image processing, model deployment, and retrieval-augmented
generation (RAG) on Red Hat OpenShift AI.
This workshop provides a hands-on introduction to building AI-enhanced applications using a
combination of large language models, image processing, model deployment, and retrieval-augmented
generation (RAG) on Red Hat OpenShift AI. Participants will explore how multiple
AI/ML technologies can be integrated into an end-to-end prototype workflow, including
sentiment analysis, prompt engineering, image recognition, model training and deployment, and
web application integration. The session combines presentations and practical exercises to
demonstrate both the user experience and the underlying architecture, while also discussing
how these patterns can be extended into scalable, production-ready AI applications.
No previous AI or development experience is required to participate.
Verena Schiffer has a background in Computer Science and has spent many years working as
an R&D engineer across a wide range of disciplines — from data science to VR/AR
technologies and later focusing on DevOps and Platform Engineering. At NTS Netzwerk
Telekom Service AG, Verena works as a Project Manager, focusing on organizational
enablement, helping translate customer needs into practical technical solutions and scalable
platforms.
“If something feels hard, start by breaking it into smaller, easier pieces.”
David Monschein is a Datacenter-Systems-Engineer at NTS Operation Center with a special
focus on NetApp and Redhat Openshift technologies. He implemented scalable automation that
eliminates repetitive work and boosts team efficiency.
Dino Begicevic is an experienced Platform Engineer at NTS, conference speaker working with Kubernetes, Terraform and Ansible – plus whatever weird problem lands in his inbox, which will be tackeled immediately!