UX Design
AI Dining Assistant
Eat by Mood
A concept driven app that helps users choose meals based on their mood, cravings, and daily goals using AI assistance and gamification.
The Project
All About Project
"AI Dining Assistant" is a conversational design concept built for Google Assistant. It uses tone detection and mood inputs to suggest restaurants, recipes, and quick bites that match the user's feelings — turning decision-making into a fun, guided experience.
What's Includes
Key Features
A summary of the main strengths of this project. These features reflect the decisions made during the design process to create a clear, intuitive, and meaningful products.
Mood-Based Filtering
Let users discover meals by choosing moods like Comfort, Adventure, or Romantic.
Gamified Meal Selection
Spin the Mood Wheel adds fun to meal discovery with AI-generated challenges.
Smart Voice Assistant
Integrates with Google Assistant for quick voice interactions.
Personalized Feedback
Learns from past moods to refine suggestions over time.
How?
The Process
What we did, how we did it, and the process we followed. We carefully planned each step, ensuring that every action aligned with our goals.
Research & Discovery
User surveys revealed that 82% of people struggle to decide what to eat daily. Existing apps like Zomato or UberEats lacked emotional or personality-based filters, creating an opportunity for a new, mood-driven approach.
Ideation & Design
I mapped out AI conversation flows, built mood personas, and prototyped the "Google Dine" interface with six moods — Comfort, Adventure, Chill, Romantic, Budget, and Quick Bite.
Prototyping & Testing
High-fidelity mockups were designed using Material UI. I tested tone detection accuracy and refined the journey flow based on peer and mentor feedback.
Outcome
Created a fully interactive UX case study prototype showing how emotional data can drive smarter dining experiences. This concept highlights the power of combining AI logic, gamification, and emotional UX.
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