Case Study
YAKO Finance
Designing an AI-powered personal finance product that makes financial information easier to understand and act on.
Selected product screens
Context
YAKO Finance is an owned product in active development. It gives YAKO a real environment for making product, design and engineering decisions rather than presenting speculative client work.
Problem
Personal finance tools often split information across disconnected views or overwhelm people with detail. The product explores how money tracking, investments and goals can exist in one calm experience.
Product direction
The current direction is mobile-first, uses progressive disclosure and treats AI as optional assistance for understanding—not as financial advice or an autonomous decision maker.
Key decisions
- Keep financial states readable before adding depth
- Separate implemented capabilities from planned work
- Use AI only where it supports a clear user decision
- Design mobile flows before expanding desktop views
Design system
A restrained Crystal UI system combines high-contrast financial hierarchy, reusable cards, calm data visualization and consistent states across mobile and supporting desktop views.
Technical foundation
The application foundation uses Flutter and Dart, with Firebase and AI integration represented only where they are part of active implementation. Security and synchronization work remains in progress.
- Flutter
- Dart
- Firebase
- AI integration
Current implementation
Implemented
- Core navigation structure
- Overview and analytics interface states
- Responsive mobile component system
In progress
- Finance tracking flows
- Investment and goal views
- Secure synchronization architecture
Planned
- Validated AI-assistance boundaries
- Representative-user testing
- Release readiness and support model
Constraints
- ConstraintThe product is not publicly released and has no production outcome metrics.
- ConstraintFinancial data shown in illustrations is intentionally neutral and non-personal.
- ConstraintPlanned AI capabilities must be validated before they are presented as available.
Honest learnings
Financial interfaces need restraint. Clear language, status transparency and responsible AI boundaries matter as much as feature depth.
Next improvements
Validate the core flows, complete secure synchronization, refine the AI safety model and test the product with representative users before any public release.
Current product scope
- Finance tracking
- Investment overview
- Goal planning
- Analytics
- AI-assisted insights
- Secure data architecture in progress