Build a Full-Stack GenAI Project in 4 Hours (FastAPI, React, Supabase)

Want to start freelancing? Let me help: https://go.datalumina.com/rWzGBfV Want to learn real AI Engineering? Go here: https://go.datalumina.com/WIQKDxv 🔗 GitHub Repository https://github.com/daveebbelaar/document-copilot Writing AI prompts all day? 🎙Try Glaido, the #1 voice dictation app for developers: https://get.glaido.com/dave ⏱️ Timestamps 0:00 Full Stack GenAI Project Overview 4:32 Client Brief and SEC Data 18:45 Project Stack and Architecture 28:34 Implementation Plan and Environment Setup 43:42 Backend Foundation and Database 1:08:15 Frontend Auth and Chat 1:34:49 Ingestion Chunking and Embeddings 1:59:52 Retrieval and Grounding 2:20:05 Frontend Integration and Citations 2:50:17 Deployment Readiness and UI Polish 2:59:50 Railway Deployment 3:34:28 Final App Walkthrough 3:45:00 Production Improvements and Wrap Up 📌 Description In this full stack GenAI project tutorial, we build a Document Copilot from scratch: a RAG application that lets users ask questions over SEC filings with grounded answers, citations, and chat history. You will see the complete AI engineering workflow with FastAPI, Supabase Postgres, pgvector, React, TypeScript, Tailwind, shadcn/ui, document ingestion, embeddings, hybrid search, and Railway deployment. This end-to-end build shows how frontend, backend, database, ingestion pipeline, retrieval, and agentic AI workflows come together in a real production-style GenAI application. 👋🏻 About Me Hi! I'm Dave, AI Engineer and founder of Datalumina®. On this channel, I share practical tutorials that teach developers how to build production-ready AI systems that actually work in the real world. Beyond these tutorials, I also help people start successful freelancing careers. Check out the links above to learn more!