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Inside the Notebook Studio AI study platform codebase

Inside the Notebook Studio AI study platform codebase

How the Notebook Studio codebase turns uploaded sources into grounded AI chat, audio overviews, mind maps, flashcards, and quizzes.

Notebook Studio is a notebook based AI study platform powered by Google Gemini. A user uploads their study material, chats with their sources, and turns any subject into audio overviews, data tables, mind maps, reports, flashcards, and quizzes. This is how the codebase makes that happen.

The workspace model

The product is organized around notebooks. Each notebook holds files, links, and search results, and every conversation is grounded in those sources. That grounding is what makes the answers useful instead of generic.

What ships inside

The codebase includes the full study loop:

  • A notebook based AI study workspace
  • Per notebook AI chat grounded in your sources
  • Studio tools: audio overviews, data tables, mind maps, reports, flashcards, and quizzes
  • Source upload for files, links, and Google search with Convex storage
  • Recurring subscriptions through Stripe, PayPal, Razorpay, and Flutterwave
  • An admin panel with usage stats, billing config, and featured notebooks
  • Five languages built in: English, German, Spanish, French, and Italian

The stack is Next.js 16, React 19, TypeScript, Convex DB, Google Gemini, Better Auth, and Tailwind CSS v4. Per user data ownership and a working subscription billing loop are included, which are the two hardest parts to build from scratch.

Why the billing loop matters

A study product lives or dies on subscriptions. The codebase ships a working recurring billing setup across multiple gateways, so your first users can pay on day one. That is the difference between a demo and a business.

See the live demo and the product page for the full capability list. Clone it, rebrand it, and you have a launchable study platform.