Nicolas KleinSpeaker
Topics
Artificial Intelligence
Learn how to reliably test and monitor GenAI applications
Generative AI opens up new possibilities—but the journey from prototype to reliable product comes with its own set of challenges. GenAI-Ops (Generative AI Operations) helps ensure the quality, reliability, and security of AI applications in production.
Whether you are working with changing LLMs, dynamic RAG systems, or autonomous AI agents, how can you reliably test results, control costs, and transparently monitor complex processes?
In this webinar, we will present practical approaches to help you operate your GenAI applications efficiently and optimize them in a targeted way.
What you will learn in the webinar
Use evaluations (evals) and LLM-as-a-Judge approaches to detect hallucinations—even after switching models.
LLMOps in practice: version prompts and track changes.
Use guardrails to protect against prompt injection, keep token costs under control, and stay on top of the EU AI Act.
Use observability to track every step and identify errors more quickly.
Who should attend this webinar?
This webinar is aimed at professionals and decision-makers who work at the intersection of software development and artificial intelligence or are interested in the topic. It is ideal for:
Software developers and DevOps/MLOps engineers who build and operate GenAI applications.
Product managers and business stakeholders who want to understand the potential of GenAI and the operational challenges it presents.
Technical leaders responsible for the strategic and sustainable implementation of AI solutions.
No in-depth knowledge of machine learning is required. A basic understanding of software development and product life cycles is sufficient.
Nicolas Klein is Technology Manager AI & Data at Ergosign. He combines a broad range of technology experience with his passion for artificial intelligence. His career has taken him from embedded systems for industrial applications to mobile app development in the public sector.
Today, his focus is on making the potential of AI accessible and useful in practical applications. He aims to enhance human expertise, make workflows more efficient, and create more room for creative and strategic tasks.
