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In this video, I build an end-to-end Text-to-SQL chatbot that converts plain English questions into SQL queries and executes them on a real database - just like a production-grade analytics system. This is not a toy demo. This is how AI-powered data systems are actually built in the real world. ⚙️📊 🧠 What’s inside this project? ✅ AWS Lambda as the main orchestrator ✅ GPT-4.0 Mini for English ➜ SQL translation ✅ PostgreSQL as the database ✅ AWS ElastiCache (Redis) for exact-match query caching ⚡ ✅ EC2 + Streamlit frontend application ✅ Real-world system design & architecture patterns 🏗️ Architecture Flow 🧩 User enters a question in plain English 🧠 GPT converts it into a SQL query 🗄️ SQL is executed on PostgreSQL ⚡ Cached responses are instantly returned using Redis ☁️ Fully deployed using AWS services 💻 GitHub Repository 🔗 https://github.com/adichatterjee/SQLA... 🔗 Let’s Connect (More Content Like This 👇) If you enjoyed this build and want more real-world AI + data engineering content, follow me on LinkedIn and this channel where I regularly share: 📌 End-to-end system architectures 📌 Hands-on AI & LLM projects 📌 AWS & data engineering insights 📌 Career-focused tech content 🔗 LinkedIn: / adityachatterjee92 🎯 Who is this video for? 👨💻 Data Engineers 📊 Analytics Engineers 🤖 AI / LLM Enthusiasts ☁️ AWS Developers 🧠 Anyone building production-ready AI applications 👍 Like the video if this helped 🔔 Subscribe for more hands-on AI + AWS projects 💬 Comment what you want to extend next - scaling, security, or accuracy!