Real-life GenAI: (My) RAG system, from prototype to production ready

Generative AI is currently on everyone’s lips. Thanks to suitable frameworks and libraries, a simple Hello World-level solution can be set up quickly. Unfortunately, these kind of solutions are far from meeting the requirements of real-world applications.

During this workshop, we will build our own GenAI solution step by step in the form of a RAG-based system (Retrieval Augmented Generation) for querying domain-specific expertise. In doing so, we will deliberately run into common pitfalls, subject our solution to a reality check, and use the insights gained to improve our system.

In the end the result is a GenAI-based RAG system that can be used in practice with confidence – as an integrated solution, aka “AI-as-a-Service,” for multiple languages in parallel with role-based access permissions to the underlying data.