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AI-Powered Food Discovery Mobile Application Development
  1. case
  2. AI-Powered Food Discovery Mobile Application Development

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AI-Powered Food Discovery Mobile Application Development

diffco.us
Food & Beverage

Challenge

Foodies struggle to find restaurants that perfectly match their tastes due to overwhelming choices and unreliable reviews. Existing restaurant discovery apps often lack personalized recommendations and deep insights into culinary experiences. Users spend significant time researching and comparing restaurants, and often rely on multiple review platforms.

About the Client

Fredd AI is a technology company focused on providing an intelligent mobile application for food enthusiasts to discover and explore restaurants based on personalized preferences and expert recommendations.

Objectives

  • Develop a user-friendly mobile application that provides personalized restaurant recommendations.
  • Integrate AI algorithms to analyze user preferences and provide relevant suggestions.
  • Aggregate and analyze data from multiple review platforms to provide comprehensive restaurant information.
  • Offer smart collections and curated lists of restaurants based on various criteria.
  • Provide accurate and up-to-date restaurant information, including menus, photos, and pricing.
  • Enhance the user experience by calculating travel time and providing route guidance.

Functional Requirements

  • User profile creation and preference setting
  • AI-powered restaurant recommendation engine
  • Restaurant search with filtering options (cuisine, price, rating, etc.)
  • Detailed restaurant profiles (photos, menus, reviews, team information)
  • Smart collections and curated restaurant lists
  • Real-time travel time calculation and route guidance
  • User reviews and ratings
  • Social sharing functionality
  • Restaurant management interface for owners

Technology Stack

iOS Native Development (Swift)
API integration (Zagat, Yelp, TripAdvisor, Zomato, Foursquare, Michelin)
AI/Machine Learning algorithms
Google Maps API
Caching mechanisms

External Integrations

  • Facebook API (for user authentication and social sharing)
  • Google Maps API (for location services and route calculation)
  • Various restaurant review platform APIs

Non-Functional Requirements

  • Scalability to handle a large user base and growing restaurant database
  • High performance for fast search and recommendation results
  • Secure data storage and user privacy
  • Reliable real-time travel time calculation
  • User-friendly and intuitive interface

Business Impact

This application is expected to increase user engagement with restaurants, drive traffic to local businesses, and enhance the overall dining experience. The AI-powered recommendations and comprehensive restaurant information will provide significant value to food enthusiasts, leading to increased app usage and revenue generation through potential partnerships and advertising opportunities. The application will also empower restaurant owners to better connect with their customers and manage their online presence.

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