Detailed breakdowns of real projects: challenges faced, solutions built, and results achieved. Each case study shows my approach to full-stack development, AI integration, and product thinking.
AI-powered document intelligence with RAG and real-time chat
Next.js, LangChain, OpenAI, Vector Database, Tailwind CSS
8 weeks from concept to launch
Live in production with active users
A cutting-edge RAG application that lets users ingest websites and chat with the content using natural language. Demonstrates full-stack capabilities: semantic search, real-time processing, and AI integration.
Read Full Case StudyProduction-grade tool for PDF manipulation and conversion
Next.js, TypeScript, PDF.js, Tailwind CSS, Vercel
6 weeks from design to launch
Live with regular users
A fully functional SaaS tool for PDF processing: merge, split, reorder, and convert documents. Shows real-world full-stack development with file handling, performance optimization, and user-friendly interface.
Read Full Case StudyBeyond the detailed case studies above, I've built several other projects showcasing different skills:
Streamlit app for AI-assisted flight search and booking. Shows Python backend, natural language processing, and Streamlit UI.
View live →Generate synthetic data for ML projects. Demonstrates Python, AI/ML integration, and data generation techniques.
View live →From frontend UI design to backend optimization, database architecture, and deployment.
Practical experience with LLMs, RAG systems, vector databases, and real-time processing.
Not just code—understanding user needs, UX design, and building products that users want.
Explore additional projects in my portfolio and GitHub repositories.