Bite Buddy

AI that decodes your plate into calories, macros, and healthier choices.

Team lazrus
Introduction and Product Overview

Bite Buddy is an AI-powered nutritional tracking and recommendation platform designed to empower users with immediate, ingredient-aware insights into the food they consume. Our mission is to bridge the awareness gap in nutritional understanding through cutting-edge technology.

The Problem We Solve

The Awareness Gap

Many individuals lack consistent, real-time awareness of their meal's calorie and nutrient content, leading to inconsistent energy levels, poor dietary habits, and reduced focus throughout the day.

Escalating Health Risks

High-risk consumption patterns, characterized by macronutrient imbalance, contribute to the rapid emergence of Non-Communicable Diseases (NCDs), including high blood pressure, elevated cardiometabolic risk, and obesity.

Current Public Health Challenges

  • High rates of child stunting (34.7%) and wasting (17.3%) indicate ongoing nutritional deficits
  • Rising prevalence of teen overweight and obesity increases long-term risk of type-2 diabetes
  • Significant adult diabetes prevalence (9.0% women, 10.2% men) highlights the national crisis
Target Audience & Outcomes

Who We Serve

Individuals across all demographics, primarily teenagers and adults, who are actively seeking to manage their diet, improve nutritional literacy, and achieve specific health and wellness goals.

Demonstrated Benefits

AwarenessImproved Nutritional Understanding
PreventionReduced Risk of Lifestyle Diseases
HabitsHealthier Eating Patterns
InsightsQuick, Personalized Diet Data
EmpowermentSelf-Directed Management
How Bite Buddy Works
Hybrid AI Architecture: CNN + Vision Transformers for high accuracy and scalable food recognition
1

Food Image Capture

User provides a simple photo of their plate as the primary input

2

Food Segmentation

AI isolates and identifies every individual ingredient/component (rice, broccoli, chicken, sauce)

3

Dish Classification

System determines overall dish type (salad, stew, sandwich) for contextual analysis

4

Nutritional Mapping

Cross-referenced with comprehensive nutritional databases for accurate data retrieval

Key Features

Calorie & Macro Estimation

Precise estimates for calories, protein, fats, and carbohydrates based on detected foods

Portion & Cooking Adjustment

Ingredient-aware predictions factoring portion sizes and cooking methods

Healthier Alternatives

Contextually relevant recommendations for improved dietary choices

Feasibility & Compliance

Technical Feasibility

  • • Hybrid AI (CNN + ViT) model ensures accuracy
  • • Proven approach for scalable food recognition
  • • Low friction user experience
  • • Instant nutritional results

Business & Legal

  • • Cost-effective development approach
  • • Leverages existing ML models
  • • Legal & compliant data sourcing
  • • Full regulatory compliance

Data & Scalability

Currently using reliable open-access datasets with architecture designed for scalability to high-integrity licensed resources like IFCT 2017. The platform supports multi-component dishes and allows easy addition of new food items or regional cuisine data.

User Guide

Getting Started

Simply capture an optimal photo of your meal for analysis. Ensure good lighting and clear visibility of all food items.

Interpreting Results

Review the segmentation map, understand the calorie and macro breakdown data, and explore the detailed nutritional analysis.

Actionable Insights

Apply the healthier alternative suggestions to future meal planning and make informed consumption decisions.

Summary

Bite Buddy combines high-accuracy AI with personalized, actionable nutrition advice to address the critical gap in nutritional awareness. Our platform empowers users to make informed dietary choices, reduce health risks, and develop sustainable eating habits through innovative technology.

Team lazrus - 2025