Nov 8, 2025

EatRight AI

flutter firebase gemini getx genkit

EatRight AI is a mobile application built with Flutter, designed to help users understand and manage their nutrition through powerful AI-driven analysis and intuitive tracking features.

✨ Key Features

  • 🤖 AI Meal Analysis:
    • Analyze meals by capturing an image or providing a text description.
    • Identifies individual food items and estimates quantities.
    • Provides detailed macro- and micronutrient breakdowns for items and the total meal.
  • 🏷️ AI Product Label Analysis:
    • Scan both the product front and the nutrition label using images.
    • Extracts product name, brand, serving size, ingredients, allergens.
    • Provides detailed nutritional information per serving, including health impact assessment based on Daily Values (DV).
  • 📝 Consumption Logging:
    • Easily log analyzed meals or products to your daily intake.
    • Specify consumed servings for accurate tracking of product consumption.
    • Records consumption time.
  • 📊 Daily Intake Tracking:
    • Aggregates logged food items into a daily summary.
    • Tracks total calories, protein, carbs, fat, fiber, and potentially other nutrients.
    • Provides a breakdown of calorie intake by meal type (Breakfast, Lunch, Dinner, Snacks).
    • Visualizes progress towards daily goals (based on DVs).
  • 💬 Contextual AI Chat ("Ask AI"):
    • Engage in a conversation with the AI assistant specifically about the meal or product you just analyzed.
    • The AI context includes the detailed analysis data and general DV guidelines for relevant answers.
  • 👤 User Profiles:
    • User authentication and profile management.
    • Stores user details, preferences, and potentially health goals (future enhancement).
  • 📶 Offline-First Data:
    • Utilizes local caching for daily summaries and consumption details, ensuring app usability even without an internet connection.
    • Asynchronous background synchronization with Firebase Firestore for data persistence and multi-device access.

This build was uploaded as a hackathon project

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    Saturday, Nov 8th, 2025