It's said that context is king. This phrase has become more important in recent times thanks to the rise of AI and LLMs. LLMs are evolving faster and faster every month. However, trained models lag in knowledge regarding recent events as well as specific data pertaining to your business, specially those models trained externally. This being said, there are ways to enhance these models with additional context enabling them to deliver results custom tailored to your specific needs.

In this session we'll have a look at how we can achieve this goal using a combination of well known Java stacks and libraries such as Spring AI and LangChain4j.