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OVERVIEW



The everyday question “What are we eating today?” has become a shared struggle. This platform reimagines that decision as a more emotional, intuitive experience rather than a routine task.






For many busy workers and college students, eating has become a routine rather than a moment to enjoy.  Studies show that nearly
80% of adults feel too tired to cook after work, and > 50% of Gen Z often eat while multitasking.
PROBLEM STATEMENT






How might we make eating feel comforting and joyful again for people who are too busy or tired to enjoy their meals?





 


THE FIVE WHY’s




                   VALUE PROPOSITION WHAT IS POMI?

Pomi is an AI-powered dining platform that helps people choose where     to eat based on how they feel. It simplifies decision-making through personalized restaurant suggestions, turning everyday dining into a thoughtful experience.





KEY FEATURES





Smart Meal Flow
Guides users step by step to choose the most comfortable way to eat based on their current situation.







Food Journey
Allows users to log meals with location, mood, and notes, creating a personal memory on map so users can revisit for comfort and reflection.







Dietary Preferences 
Set personal dining preferences in advance so users receive restaurant suggestions that match their tastes, restrictions, and moods effortlessly.





COMPATITIVE ANALYSIS

I looked at both direct and indirect competitors to understand how existing solutions handle dining decisions and where new value could be created





PERSONA

EMPATHY MAP

USER JOURNEY


  
BUSINESS MODEL CANVAS




INFORMATION ARCHITECTURE




MID-FIDELITY WIREFRAME




USER TESTING & SYNTHESIZE


To validate the concept and understand how users perceive its value, I conducted a concept testing session focusing on the overall idea, core features, and emotional experience of the app.


USER FEEDBACK

01Clarify Structure and Flow
Users found parts of the interface unclear and overlapping. They suggested simplifying navigation and creating a more intuitive structure across the app.


02Strengthen Core ExperienceParticipants emphasized making the decision process more effortless, distinctive, and emotionally engaging, focusing on features that truly enhance dining experiences.

03Improve Personalization and RelevanceUsers wanted smarter filtering, more meaningful AI suggestions, and personalized summaries that better align with their preferences and contexts.

04
Make Food Journey More PlayfulUsers hoped the record and reflection features, such as Food Journey, could become more visual, interactive, and fun to revisit.




SOLUTIONS