Matthias Boeck
Dr. Matthias Böck holds a doctorate in bioinformatics and machine learning and has been working as a data scientist in the Data Product department at the Munich-based consultancy FELD M since 2013. He is the technical manager for projects in the fields of machine learning and data strategy. He is the author of specialist books on AI, holds design thinking workshops and works with universities on research projects. In addition to these fields, he is also involved in the topic of data for good and its use in practice.
Session
Retrieval-Augmented Generation (RAG) systems are transforming how we interact with unstructured data using Large Language Models (LLMs). While it’s now relatively easy to stand up a basic RAG prototype, deploying a robust, customizable, and production-ready system remains challenging.
In this talk, we present our open-source RAG blueprint through the lens of a real-world application: Bundestag Chat—a system that enables users to explore and converse with German parliamentary speeches. We’ll demonstrate how the blueprint streamlined development and scaling, and how its modular architecture allowed for seamless integration of components like LlamaIndex, Hugging Face embeddings, PGVector, Langfuse, and Ragas.
Attendees will walk away with practical insights into customizing RAG pipelines for real use cases, whether building internal tools or user-facing applications. We’ll also explore build-vs-buy trade-offs, retrieval and scaling strategies, and considerations around privacy, evaluation, and monitoring.