Passage capture
Review a user-provided excerpt with OCR corrections and a saved-source label.
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- Reading companion
- AI mobile concept
Readquill
A reading companion for source-grounded discussion, personal annotation search and generated recall practice.
Designed around4 AI workflows
Project overview
Readquill explores reading companion through a mobile experience built around an excerpt-first reading view with a collapsible discussion sheet. A reading companion for source-grounded discussion, personal annotation search and generated recall practice. The proposed journey connects passage capture, discuss passage, recall cards, reading trail. Four original phone showcases establish the visual direction, while the case study defines the supporting feature set and a proposed Kotlin architecture.
The challenge
Readers need AI explanations grounded in passages they provide and a clear way to preserve their own interpretation. On a phone, the person also needs to capture information quickly, understand where an answer came from and return to the original material without navigating through a dense desktop interface.
- Keep passage capture and discuss passage connected within a short mobile flow.
- Make passage extraction correctable when the model misreads the input.
- Explain recall generation through visible references or user-selected preferences.
- Keep changes, sharing and data retention under explicit user control.
Our solution
The design begins with an excerpt-first reading view with a collapsible discussion sheet, using large touch targets, short task sequences and contextual sheets. Turn a photographed user-provided excerpt into editable text. Explain selected passages with visible source anchors. The companion views keep drafts, original material and accepted decisions distinct. A cream, oxblood and charcoal visual system gives this app its own character within the collection.
- Turn a photographed user-provided excerpt into editable text.
- Explain selected passages with visible source anchors.
- Draft self-check questions from the chosen material.
- Find connections among the reader's own saved annotations.
Key features
Inside the platform
Keep the question close to the passage.
Original mobile interface concepts with fictional content. AI responses illustrate proposed interactions; they are not live model results.
Proposed technology stack
Proposed Android architecture using Kotlin and Jetpack Compose. AI processing, storage and synchronization are design proposals for this concept, not integrations implemented by this portfolio.
- Kotlin
- Jetpack Compose
- Room
- AI services
The results
The concept defines four mobile views, four AI workflows and twelve feature areas. The next validation would ask a user to complete passage capture, inspect the proposed discuss passage output and correct an intentional extraction or suggestion error. Evaluation would focus on source traceability, correction effort and task completion. No usability study or business-impact measurement is claimed.
4Original mobile showcase views
4Proposed AI workflows
12Designed feature areas
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