We are seeking an experienced development team or freelancer to build an AI-powered web and mobile application designed to transform student study notes into interactive practice quizzes. This automated learning assistant will enable students to upload their handwritten or typed study materials (PDF, image, or text) and automatically generate various types of quizzes, including multiple-choice questions (MCQs), short answer questions, and flashcards.
Core Features:
- Multi-Format Document Parsing: The application must be capable of ingesting PDFs, raw text files, and images of handwritten notes, utilizing Optical Character Recognition (OCR) for image-based content.
- Automated Assessment Generation: An integrated Large Language Model (LLM) will process the uploaded content to construct structured, curriculum-aligned assessments. This includes generating MCQs, fill-in-the-blanks, true/false, and conceptual short-answer items based strictly on the source material.
- Instant Feedback & Explanations: Users will receive immediate feedback on their answers, along with clear explanations for correct and incorrect responses, referencing specific sections of their uploaded study material.
- Flashcard Mode: The system should automatically extract key terms, formulas, and definitions from the notes to create interactive digital flashcards.
- Performance Analytics: A visual dashboard will track student progress, including topic retention, recurring weak points, and test completion rates over time.
Proposed Tech Stack:
- Frontend: React /
Next.js (Web) or Flutter / React Native (Cross-platform Mobile)
- Backend:
Node.js (Express/Fastify) or Python (FastAPI)
- AI & Document Processing: Integration with OpenAI API / Anthropic Claude API / Google Gemini API, utilizing LangChain/LlamaIndex for Retrieval-Augmented Generation (RAG architecture), and Tesseract OCR / Google Cloud Vision for image extraction.
- Database & Storage: PostgreSQL for user profiles and quiz history, AWS S3 / Supabase Storage for note uploads, and Pinecone / pgvector for vector search in document retrieval.
Delivery term: Not specified