RAG in the wild: real-world lessons from modernizing legacy systems
Byte size (INTERMEDIATE level)
Zaal 10
Enterprise and government document systems hold terabytes of valuable unstructured information, yet most still rely on keyword and metadata search with little semantic context. Retrieval-Augmented Generation (RAG) promises a breakthrough, but tutorials rarely prepare you for regulated, large-scale environments.
In this talk, I’ll share lessons from building a RAG stack with Spring Boot, Elasticsearch, LangChain4j, Docker, and ActiveMQ, using both Azure OpenAI and Ollama. Expect concrete learnings on document chunking, enforcing access control, and keeping LLMs grounded in facts. Practical takeaways for anyone bringing RAG from demo to production.
In this talk, I’ll share lessons from building a RAG stack with Spring Boot, Elasticsearch, LangChain4j, Docker, and ActiveMQ, using both Azure OpenAI and Ollama. Expect concrete learnings on document chunking, enforcing access control, and keeping LLMs grounded in facts. Practical takeaways for anyone bringing RAG from demo to production.
Susanne Pieterse
Open.nl Software Group
As an autodidact full-stack engineer and iSAQB-certified software architect, Susanne thrives on innovation, learning, and knowledge-sharing, with tea and a heavy-bag boxing workout fueling the journey. She helps Java developers, who are eager to explore generative AI, transform their ideas into high-value, real-world creations.