So, you have created your first AI application. Congratulations! But how do you scale, operate, maintain, and grow it within your enterprise? This is the challenge that many organizations face today. Machine learning models cannot live on their own and have to be incorporated into the production environment. 

Generative AI solutions: To make things worse, programming frameworks, tools and infrastructure are evolving at an enormous pace. Luckily, new architectures, tools, and design pattern have arrived to work with these new technologies. One important field of research is MLOps (with speciality LLMOps for large language models), which has evolved into a way of working and set of best practices to deploy, test, manage, and monitor machine learning models in production. 

In this session, Bas will present a reference architecture that can be applied to any machine learning or generative AI project, with some examples from the real world and practical tool advice. Based on this information you should be able to create your own solution architecture and reason about the technology options. Join this session to learn how to build a robust and scalable AI platform that meets the needs of your enterprise!