Thought inbox
Review voice, photo and text capture cards with a prominent Add thought control.
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- Personal knowledge organizer
- AI mobile concept
Agendalith
A personal knowledge app for multimodal capture, cited archive search and editable connections between ideas.
Designed around4 AI workflows
Project overview
Agendalith explores personal knowledge organizer through a mobile experience built around a knowledge-card canvas with voice inbox and relationship view. A personal knowledge app for multimodal capture, cited archive search and editable connections between ideas. The proposed journey connects thought inbox, ask my archive, connection map, weekly reflection. Four original phone showcases establish the visual direction, while the case study defines the supporting feature set and a proposed .NET MAUI architecture.
The challenge
People collecting notes need grounded retrieval and editable connections without opaque AI rewriting of their personal archive. 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 thought inbox and ask my archive connected within a short mobile flow.
- Make multimodal capture correctable when the model misreads the input.
- Explain connection suggestions through visible references or user-selected preferences.
- Keep changes, sharing and data retention under explicit user control.
Our solution
The design begins with a knowledge-card canvas with voice inbox and relationship view, using large touch targets, short task sequences and contextual sheets. Draft searchable text from voice notes and photographed writing. Answer from selected folders with visible note references. The companion views keep drafts, original material and accepted decisions distinct. A midnight violet, mint and pearl visual system gives this app its own character within the collection.
- Draft searchable text from voice notes and photographed writing.
- Answer from selected folders with visible note references.
- Propose relationships with explanations the user can reject.
- Draft a digest while preserving the source notes unchanged.
Key features
Inside the platform
Find the thought you saved for later.
Original mobile interface concepts with fictional content. AI responses illustrate proposed interactions; they are not live model results.
Proposed technology stack
Proposed modernization architecture: .NET MAUI and C# for iOS and Android, with Xamarin shown as the legacy migration source. AI services and offline storage are design proposals; this portfolio entry is not a shipped application.
- .NET MAUI
- C#
- Xamarin (legacy)
- 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 thought inbox, inspect the proposed ask my archive 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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