Inspiration

Every reader knows the habit: you come across a line that stops you in your tracks, snap a quick photo with your phone, and keep reading. But over time, those photos get buried in a crowded camera roll; you forget the quote, you forget the photo, and you certainly forget where to find it again. Book clubs face an even bigger hurdle: keeping group chats alive. Because reading is an inherently solitary activity, maintaining continuous engagement between meetings is notoriously difficult. Group chats quietly fade away, momentum stalls, and the shared excitement of a book dies down. With Quobe, we experimented with a brand-new way to talk about books using the very words of your favorite authors. Instead of getting lost in digital clutter, highlighted quotes become effortless conversation starters. They transform static passages into the primary driver of club interaction, keeping group chats active, inspiring members to pick up their books, and giving everyone a natural, visual way to share where they are in the story. Quobe ensures no great line is ever forgotten, turning solitary reading into a connected, living community.

What it does

Quobe reimagines the relationship between physical reading and digital community through a suite of carefully crafted features designed to make sharing books as rewarding as reading them:

Asynchronous Clubs & Passage-First Feed Readers join private book clubs using native iCloud invite links. Within the club feed, posting a quote acts as both a meaningful message and an ambient update on your reading progress, giving friends a natural glimpse into what page you are on and inviting them to react with emojis or start a conversation.

Instant Page Scanning & OCR Rather than manually typing out long passages, Quobe’s camera scanner turns physical pages into digital text in seconds. Simply tap a sentence to select your highlight—our on-device text recognition isolates your favorite lines, eliminating typing friction entirely.

The "Paper & Ink" Card Engine Captured passages are instantly transformed into high-fidelity, customizable quote cards. Readers can tailor every aesthetic detail pairing literary typography with tactile paper textures, rich color gradients, and custom text alignments. Designed for effortless sharing, cards export in native 9:16 formats for Instagram Stories and WhatsApp, or publish directly to your club feed.

Automated Library Organization Cataloging your collection is completely frictionless. You can add books by scanning a physical barcode or searching by title. Quobe communicates with the Open Library API to automatically retrieve cover art and author metadata, organizing your collection into clean "Reading," "Read," and "To Read" shelves.

Zero-Account, Privacy-First Sync Quobe operates with zero forced account registration. Your reading history, quote archive, and club memberships live within your personal Apple iCloud ecosystem (CloudKit), syncing transparently across all your iOS devices while ensuring your personal reading data stays strictly yours.

How we built it

We are a team of three developers handling design, product management, and core engineering. Drawing from our own frustrations as readers, we kicked off the project with rapid wireframing,using the Crazy Eights design sprint method, to distill our ideas into a tightly scoped MVP. To accelerate our timeline, we leveraged generative AI alongside our product specs to bootstrap initial UI/UX concepts. Our designer then heavily iterated on these baselines over this month, polishing them into a clean, human-centered interface. We also integrated AI tools into our development workflow, ensuring all generated code strictly adhered to The Composable Architecture (TCA). Every feature operates as an isolated reducer with explicitly injected dependencies (OCR, CloudKit sync, ad policies), keeping the codebase modular and testable. Data persistence and cross-device sync rely on SQLiteData and GRDB using type-safe StructuredQueries, streaming state changes to Apple CloudKit across both private and shared database zones. Live page scanning and barcode parsing are powered by the Vision framework, paired with an on-device language model (via Apple Intelligence) to clean up raw OCR noise on book cover scans. Because Quobe is a social-first experience with a focused initial feature set, we implemented our monetization strategy using RevenueCat Ads. This allowed us to establish an early ad-revenue pipeline while keeping the core experience free and frictionless for our early adopters.

Challenges we ran into

Evolving AI-Assisted Design: Working from an AI-generated UI baseline for the first time presented a learning curve. We had to figure out how to deeply iterate on raw AI mockups without slowing down development, turning initial visual sparks into a cohesive design system that accelerated our pipeline. CloudKit Sync & Relational Data: Bridging local database engines with shared cloud records brought significant architectural hurdles. Local rows generated before initializing our CloudKit sync engine lacked system metadata, requiring us to write a retroactive backfill migration to ensure clean club merges upon invite acceptance. OCR Noise: Physical book pages are notoriously noisy, fraught with running headers, page numbers, and awkward line wraps. Filtering that visual clutter into clean, tap-selectable sentences required iterating through several custom text-segmentation algorithms.

Accomplishments that we're proud of

What we learned

Integrating ad monetization was a brand-new experience for our team. Leveraging RevenueCat Ads gave us the infrastructure to experiment with ad placements seamlessly, teaching us how to balance monetization with user experience without writing complex ad-tracking logic from scratch.

What's next for Quobe - Read Together, Highlight What Matters

Our immediate focus is on UX refinement, performance optimizations, and minor bug fixes to make the reading experience as smooth as possible. We are introducing analytics to better understand user engagement and fine-tune ads placements for minimal disruption. To expand our user base, we are preparing a targeted social media campaign aimed at digital book clubs and reading communities. Looking further ahead, our long-term roadmap includes a shift toward a hybrid monetization model, combining a premium RevenueCat subscription tier with book recommendations and ad partnerships sponsored directly by book publishers.

Built With

  • admob
  • app-tracking-transparency
  • apple-intelligence
  • cloudkit
  • google-mobile-ads
  • grdb
  • icloud
  • ios
  • kingfisher
  • layers
  • open-library-api
  • revenuecat
  • revenuecat-ads
  • sqlite
  • sqlitedata
  • storekit
  • swift
  • swift-dependencies
  • swiftui
  • the-composable-architecture
  • user-messaging-platform
  • vision
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