AI & ChatbotsFeatured work
Applied AI & Spring AI Projects
Self-directed Java and Spring AI projects exploring RAG, conversational memory, and multiple model providers.
Independent, self-directed projects I build to learn and apply practical AI engineering. These are personal projects and are not affiliated with any employer.
- Role
- Independent projects
- Domain
- Applied AI (Personal / Self-Learning)
- Timeframe
- Jan 2025 - Present · Personal
Highlights
- Multi-provider LLM integration across OpenAI, Anthropic, Gemini, and Ollama
- RAG over application-specific documents
- Conversational memory across interactions
About these projects
Alongside my professional work, I invest in hands-on AI learning through personal projects. They are self-directed and not affiliated with any employer, which lets me experiment freely with providers, patterns, and trade-offs.
What I have built
- Java and Spring AI prototypes integrating multiple LLM providers (OpenAI, Anthropic, Google Gemini) and local models via Ollama.
- Conversational memory to maintain context across user interactions.
- Retrieval-Augmented Generation (RAG) workflows that answer questions from application-specific documents and knowledge.
- Comparisons across providers covering prompt design, token usage, response quality, fallback strategies, and integration patterns.
- Experiments with local models through Ollama to understand privacy, infrastructure, performance, and cost trade-offs.
Current direction
I am now exploring agentic, tool-enabled AI for practical enterprise use cases, applying the same backend discipline I bring to any other integration work.
Technologies
JavaSpring AIRAGLLM IntegrationPrompt EngineeringOpenAIAnthropicGoogle GeminiOllama