StudyWise AI

An AI-powered study planner that creates personalized study schedules based on a student's subjects, exam dates, preparation level and available study time.

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Inspiration

Inspiration

Exam preparation often creates high anxiety due to vast syllabi and shrinking deadlines. Students spend valuable revision hours manually calculating study days and trying to prioritize topics. We built StudyWise AI to remove this planning friction, instantly transforming raw syllabus text and exam dates into an actionable, prioritized roadmap with active recall prep.

What it does

  • Dynamic Timeline Calculation: Automatically computes exact days left until the exam and distributes the study load evenly.
  • Intelligent Topic Weightage: Analyzes syllabus topics and tags them with High, Medium, or Low priority based on exam relevance.
  • Structured Daily Targets: Provides specific hourly breakdowns and actionable sub-tasks for each revision day.
  • Active Recall Testing: Generates custom practice questions for each topic to enforce effective retention.
  • One-Click Offline Export: Allows students to download their entire schedule as a .txt timetable file instantly.

How we built it

  • Backend: Developed a lightweight, responsive server using Python and Flask.
  • AI Engine: Integrated the Google Gemini API via the google-genai SDK with prompt design enforcing strict JSON outputs.
  • Frontend: Designed a modern, distraction-free UI using clean semantic HTML5, responsive CSS3, and asynchronous Vanilla JavaScript (Fetch API).
  • Security & Environment: Utilized python-dotenv to safeguard API keys and configured Git version control with .gitignore.

Challenges we ran into

  • Structured AI Outputs: Ensuring the Gemini model consistently returned structured, clean JSON without conversational markdown chatter so the frontend could render interactive cards reliably.
  • Date & Schedule Math: Managing edge cases where exams are very close, requiring adaptive load-balancing rather than overloading a single day.
  • Environment Configuration: Managing PowerShell execution policies and virtual environment paths during setup.

Accomplishments that we're proud of

  • Building a full-stack, end-to-end AI application from scratch.
  • Creating an interface that handles syllabus parsing, visual roadmap generation, and file exporting in under 5 seconds.
  • Maintaining a secure repository where sensitive credentials stay protected.

What we learned

  • Hands-on implementation of the updated google-genai SDK and modern Gemini models.
  • Parsing structured JSON responses dynamically into interactive web components.
  • Best practices in Git version control, environment isolation, and developer documentation.

What's next for StudyWise AI

  • Google Calendar Integration: One-click sync to push revision blocks directly to Google Calendar.
  • Automated Mock Quizzes: Interactive quiz modes with instant AI feedback based on syllabus topics.
  • Progress Tracking Dashboard: Allowing students to mark completed days and dynamically recalibrate the schedule if they fall behind.

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Updates

posted an update —

Building StudyWise AI: Turning Exam Anxiety into Actionable Plans

Most students don't struggle because they lack potential; they struggle because syllabus overload creates decision fatigue. When exams approach, figuring out what to study and how much time to dedicate takes up more mental energy than the studying itself.

To fix this, I built StudyWise AI — an intelligent study copilot designed to take raw syllabus topics, match them against your available time, and transform them into a structured daily execution roadmap.

What went into this build:

  • Intelligent Strategy Engine: Leveraged the Google Gemini API to analyze topic complexity and assign clear prioritization (High/Medium/Low) rather than treating every unit the same.
  • Active Recall Integration: Tailored prompt engineering ensures the output includes retrieval-practice questions, not just passive reading lists.
  • Zero-Friction Utility: Built with a clean Python/Flask backend, responsive vanilla UI, and a one-click .txt timetable download for offline tracking.

Building this end-to-end as a solo developer was an incredible learning curve — from handling prompt constraints to creating a clean student-first UI.

Excited to see where this project goes next! Feedback, suggestions, and thoughts are always welcome in the comments.

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posted an update —

StudyWise AI is officially submitted!

Built this project to solve a real student problem: managing syllabus panic before university exams.

Key Highlights:

  • Intelligent study roadmap generation powered by Google Gemini API
  • Automated topic prioritization & active recall prompts
  • One-click timetable export (.txt)
  • Lightweight, responsive UI with no heavy frontend bloat

Excited for the judging round! Feedback and suggestions are welcome in the comments.

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Submission history