In the past few months, I've spoken about building AI-powered Java apps at tens of events around the world. What I’ve seen is that Java developers are curious and eager to learn, but AI can seem like a big and daunting new area to get into. Most of us have demanding jobs that occupy our time, and we might not have had the chance to learn the new concepts and tools needed to integrate AI into the apps we’re building.
At the same time, I believe business apps are a place where AI can make a big impact. Enterprise applications are often built to support complex workflows with many manual steps. There are people who spend their days working on tasks that AI could streamline significantly.
I wanted to help Java developers get started with building AI-augmented applications by creating application starters that focus on tasks common in business settings.
Business context-aware AI chat
The first application starter is a retrieval-augmented generation (RAG) application that reads documents from a specified folder and uses them as context when answering questions. This is a good starting point for a chatbot that provides help about your business to customers or employees.
The application is built with Flow, LangChain4j, and Spring Boot. You can find the sources on GitHub.
Sentiment analysis and reply drafting
The second application performs sentiment analysis on customer feedback. It provides a UI for drafting custom responses to feedback, helping customer support representatives provide more timely responses to customers.
The application is built with Hilla, LangChain4j, and Spring Boot. You can find the sources on GitHub.
Next: Ideas wanted
Instead of trying to come up with realistic use cases on my own, I'd love to hear from you: how could AI improve your business apps? What kind of starters would you like to see next? Let me know in the comments below, or send me a message on Twitter or LinkedIn!