Easypick

Built a warm, data-driven restaurant decision-support interface that helps smart-table users choose meals through Quick Pick and Smart Pick flows.

Frontend Developer

Flows

Quick Pick and Smart Pick

Context

Shared smart dining table

Integration

Frontend-only mock data

Project overview

Easypick is a futuristic restaurant decision-support platform designed for a smart dining table with an embedded horizontal touchscreen. Instead of behaving like a typical food ordering app, it guides customers through mood-based and preference-based flows so they can choose meals quickly and confidently. Users can select a mood, tune nutrition preferences, review curated meal cards, compare two dishes side by side, receive a final recommendation, and display a QR code for ordering. The interface is warm, minimal, data-driven, and optimized for collaborative use on a shared table, reducing decision fatigue by turning a long menu into a focused interactive experience.

Key contributions

Built Quick Pick and Smart Pick flows for mood-based and nutrition-based decisions.
Designed meal cards with food imagery, nutrition stats, match labels, and compare actions.
Added side-by-side dish comparison, final recommendation reasoning, and QR confirmation.
Implemented rotate logic for 0, 90, 180, and 270 degree table interaction.