Student AI is an interactive AI-powered learning platform designed to help students learn concepts in a conversational and personalized way.

The platform allows students to directly chat with an AI tutor, ask questions, and receive contextual, easy-to-understand explanations — making learning more engaging and adaptive.

I built this system using a Retrieval-Augmented Generation (RAG) architecture, combining LLM capabilities with structured educational content to ensure accurate and relevant responses.

Key features include:

• AI-powered chat interface for real-time learning and doubt solving • RAG-based system to fetch and ground responses in relevant study material • Integration with multiple LLMs (Gemini, Ollama) for flexible AI workflows • Real-time communication using sockets for smooth chat experience • Image-based understanding and responses (visual learning support) • Context-aware conversations with session memory • Scalable backend for handling multiple concurrent users

The system is designed to go beyond generic AI chat by providing structured, curriculum-aware responses tailored for students.

Tech Stack: React / Next.js, Node.js, Socket.IO, RAG pipeline, Gemini API, Ollama, vector-based retrieval

Student AI aims to make learning more accessible, interactive, and personalized — acting as a 24/7 intelligent tutor for students.