AI-Driven Study Application & FSRS Scheduler
A full-stack, AI-augmented educational platform utilizing a custom Free Spaced Repetition Scheduler (FSRS) algorithm and local vector embeddings. Built with Flutter, Supabase, and PostgreSQL, the engine indexes textbook PDFs locally to build context-aware active recall pipelines, automatically generating high-yield study decks and quizzes without data hallucination.
The Overview
Project 2359 is a comprehensive, full-stack application designed to completely overhaul the student study loop. It merges local document analysis with a Free Spaced Repetition Scheduler (FSRS) and AI-driven content generation, built entirely around a fluid, distraction-free aesthetic experience.
The Architecture
Built on Flutter and powered by a Supabase backend with heavy PostgreSQL logic, this project prioritizes scalable system design alongside seamless front-end animations. The UI is built to feel intuitive and frictionless, ensuring the technology gets out of the way so the user can focus entirely on retention.
Core Capabilities
Implements the highly optimized Free Spaced Repetition Scheduler algorithm, dynamically adjusting review intervals based on strict cognitive retention metrics rather than arbitrary daily goals.
Users can upload massive textbooks or lecture slides. The system indexes the content locally, allowing the AI to source factual context directly from the syllabus rather than hallucinating generic internet knowledge.
Instead of manually writing flashcards, the engine analyzes the indexed PDFs and automatically generates high-yield spaced repetition decks, study guides, and active-recall quizzes.