Turning study files into active learning sessions

Quizitude converts uploaded study material into usable flashcard decks with AI-assisted question extraction. The focus is reducing setup friction between content and active revision.

The product combines ingestion, curation, and study mode into one workflow so users can go from source document to practice session quickly.

Students lose momentum between collecting and revising content

Manual flashcard creation takes time and often delays study sessions, especially when learners are working from lengthy lecture documents.

The core product challenge was to automate extraction while still preserving review quality and clear user control.

Designed around fast creation and repeatable practice

The interface uses a wizard-like flow for file upload, extraction settings, preview, and deck creation. Each stage exposes only the decisions needed for that moment.

Study mode emphasizes rhythm and feedback with a clear front/back card interaction and result summaries that support repeat sessions.

Flashcards dashboard

Study mode

Combining AI workflows with reliable data handling

Quizitude integrates document parsing with LLM-backed extraction and Supabase persistence. The architecture separates API interactions, deck logic, and UI state to keep iteration manageable.

Testing coverage and service-layer boundaries support safer updates as extraction prompts, file handling, and study logic evolve.

What this project reinforced

Building Quizitude improved my approach to AI product design where reliability and usability need to co-exist.