AI Study Hub
An exam-oriented AI platform that transforms raw academic material into structured study kits, flashcards, and viva preparation tools.
Project Overview
what
AI Study Hub is a learning-focused AI platform that converts PDFs, PPTs, and raw notes into exam-ready study kits using multi-agent AI pipelines.
why
Students struggle to convert large volumes of study material into concise, exam-oriented notes. Existing AI tools generate generic summaries that lack academic structure and reliability.
problem
Manual note preparation is time-consuming, inconsistent, and inefficient especially when preparing for theory-heavy exams requiring structured answers, definitions, and viva readiness.
Core Capabilities
Study Kit Generator
Automatically generates summaries, key topics, flashcards, and definitions aligned with exam patterns.
Exam-Oriented Answers
Produces structured 2-mark, 5-mark, and 10-mark answers with academic tone and hierarchy.
Speaker Notes & Viva Prep
Transforms PPT content into speaker notes, viva questions, and presentation tips.
Multi-Agent AI Pipeline
Uses modular AI agents for content analysis, answer generation, quality gating, and fallback handling.
Multi-LLM Fallback
Automatically switches between OpenAI and Gemini to ensure reliability under quota or rate limits.
Persistent Learning Data
All generated study kits are saved and reusable, turning AI output into long-term learning assets.
System Architecture
Frontend
Student-focused React UI with animated progress indicators and clear learning states.
Backend API
Centralized backend handling authentication, persistence, orchestration, and validation.
MCP Orchestration Layer
Manages AI workflows, tool routing, retries, and provider fallback logic.
AI Layer
LLM-agnostic architecture supporting OpenAI and Gemini with strict JSON enforcement.
Outcome & Impact
Achievements
- ✓ Stable multi-agent AI backend with persistence
- ✓ Exam-ready outputs with structured answers
- ✓ Reliable fallback across multiple LLM providers
- ✓ Clear separation of frontend, backend, and AI orchestration
Skills Gained
- → Designing production-grade AI pipelines
- → Multi-LLM orchestration and fallback strategies
- → Academic prompt engineering
- → Full-stack system architecture
Why This Matters
AI Study Hub demonstrates the ability to design reliable, exam-centric AI systems that go beyond generic summarization, focusing on correctness, structure, and real student needs.