ByteBite

MainScreen
Menu Page

Inspiration

Campus dining is confusing, unpredictable, and rarely health-friendly. Students with allergies, athletes, and people with chronic conditions struggle to know what’s safe or good for them. We wanted to fix that.

What it does

ByteBite analyzes dining-hall menus and generates personalized meal recommendations, allergy alerts, and wellness-optimized options. It supports diabetic, low-sodium, and high-protein modes, plus mood-based tracking and a gamified health avatar.

How we built it

We combined a React front-end, a Python/Flask backend, Gemini AI for analysis, and automated menu scraping. User preferences (allergies, diet, goals) feed into a ranking engine that outputs personalized scores and health warnings.

Challenges we ran into

Messy dining-hall data, inconsistent menus, API rate limits, accessibility issues, and figuring out how to personalize recommendations without overwhelming users.

Accomplishments that we're proud of

Building a fully working nutrition assistant in under 24 hours, creating real-time allergy warnings, adding chronic-condition modes, producing clean UI/UX, and delivering a product that genuinely improves student health.

What we learned

How difficult but important it is to make health data accessible. We learned a ton about nutrition scoring, allergy detection, user onboarding, and combining AI with practical wellness features.

What's next for ByteBite

Expanding more health modes (gluten-free, IBS-safe, vegan strict), adding wearable integration, calorie tracking, a campus-wide API for dining services, and releasing ByteBite as a full wellness app across colleges.