An AI-powered personalized learning companion

LearnCode AI dashboard displaying overall mastery, indexed documents, weak topics, revision reminders,and personalized study recommendations
Evaluates retrieval precision, recall, citation accuracy, and unsupported query detection.
Creates personalized revision schedules based on weak topics and mastery scores.
Tracks topic mastery, identifies misconceptions, and prioritizes revision.
Generates adaptive quizzes to assess understanding and update learner mastery.
Answers study questions using uploaded materials with verifiable source references.
Organizes study documents with topic labels, searchable content, and inspection options.
Supports PDF, PowerPoint, text, Markdown, and timestamped transcript uploads.
Combines AI tutoring, source-grounded answers, adaptive quizzes, and progress tracking.

About LearnWise AI Inspiration Students often use different resources, such as lecture videos, textbooks, and presentation slides, to prepare for exams. Finding relevant information takes time, and general AI chatbots may provide answers that are not supported by the student's learning materials. We wanted to create a personalized AI study companion that makes learning more organized, trustworthy, and effective. What it does LearnWise AI is an AI-powered learning companion designed to bring study resources together in one place. It aims to:

Process lecture videos, textbooks, PDFs, and slides.
Organize content into topics and concepts with source references.
Provide answers with citations linked to the original pages, slides, or video timestamps.
Generate quizzes and assessments based on selected topics and difficulty levels.
Track topic-wise performance, identify weak areas, and recommend personalized revision. How we built it Our planned system combines a web-based interface with AI-powered content extraction, retrieval-augmented generation (RAG), and an adaptive assessment system. Uploaded learning materials are processed into searchable content with source metadata. The tutor retrieves relevant content before generating explanations, while assessment results help estimate topic mastery and guide future learning recommendations. Challenges Key challenges include extracting useful information from different file formats, preserving accurate source references, reducing unsupported AI-generated answers, generating reliable questions and answer keys, and adapting recommendations to each student's progress. What we aim to achieve Our goal is to make self-study more personalized and reliable by connecting AI explanations directly to learning materials and helping students focus on the topics they need to improve.