Building production-ready AI applications with modern technologies. Passionate about RAG systems, vector search, and intelligent document processing.

• RAG Systems - Retrieval-Augmented Generation
• Vector Search - Semantic similarity with pgvector
• LLM Integration - Google Gemini, LangChain
• Full-Stack AI - Next.js, TypeScript, Prisma
• Production Deployment - Vercel, Supabase

Production-ready AI application for document processing and Q&A

• ✅ RAG Pipeline with LangChain + Google Gemini
• ✅ Vector Search using Supabase pgvector
• ✅ Modern UI with Next.js 15 + TypeScript
• ✅ Production Ready with comprehensive testing
• ✅ Live Demo: View Application)

Tech Stack: Next.js, TypeScript, LangChain, Supabase, Google Gemini, Prisma, Tailwind CSS

Production-ready conversational AI application with real-time streaming

• ✅ Real-time Streaming with Vercel AI SDK + Google Gemini
• ✅ Conversation Persistence using Supabase PostgreSQL
• ✅ Modern UI with Next.js 15 + TypeScript + Tailwind CSS
• ✅ Theme System with dark/light mode and localStorage persistence
• ✅ Comprehensive Testing with 66% Jest coverage
• ✅ Live Demo: View Application

Tech Stack: Next.js, TypeScript, Vercel AI SDK, Google Gemini, Supabase, Tailwind CSS, Jest

• 🔍 Advanced RAG systems with multi-modal support
• 🚀 Production AI applications with LangSmith observability
• 📚 Document processing with intelligent chunking

• Applied AI Engineer roles
• Full-Stack AI Developer positions
• RAG System Specialist opportunities
• Remote positions worldwide

⭐ Fun Fact: I've built AI applications that process documents and answer questions in real-time!