FoodSpotlight

“An AI-powered food scanner that turns confusing labels into simple, personalized insights—helping you choose healthier foods instantly.”

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Inspiration

Every day, millions of people struggle to understand what they are eating. Food labels are long, confusing, filled with chemicals, hidden sugars, additives, and ingredients most consumers can’t identify. People want to eat healthier — but the information is hard to access, harder to understand, and almost impossible to personalize.

This real-world problem inspired FoodSpotlight.

Thanks to Kiro and the incredible Kiro team for giving me the chance to turn this idea into reality. Kiro’s AI tools, smart suggestions, and fast development workflow made it possible to build, iterate, and ship features that normally take weeks — in just hours.

What it does

FoodSpotlight is an AI-powered food analysis companion that helps people make informed food choices instantly.

Users can:

Scan any food product using their phone camera

Decode confusing labels and ingredient lists

Get personalized nutrition insights based on their profile

Identify harmful or unwanted ingredients

Access AI chat for deeper health questions

Understand Nutri-Score, NOVA, and Eco-Score instantly

No more confusion. No more guesswork. Just clear, personalized answers.

How we built it

We built FoodSpotlight using:

Kiro AI for rapid development, debugging, feature exploration, and real-time coding assistance

Flutter for cross-platform UI

Open Food Facts API for verified food data

Image analysis + OCR to understand ingredients from images

AI-powered text interpretation for personalized insights

Local caching for offline support

Clean architecture + state management

Kiro AI played a major role — from generating UI components and refactoring code to optimizing barcode scanning performance.

Challenges we ran into

Parsing complex ingredient lists from low-quality product photos

Delivering personalization without overwhelming the user

Designing a clear UI that works across different screen sizes

Keeping analysis fast, even on lower-end devices

Ensuring the app feels simple despite doing a lot in the background

Kiro’s debugging tools helped solve several issues quickly, especially with Flutter layouts and API handling.

Accomplishments that we're proud of

Built a fully functional AI-powered food scanner in hackathon time

Achieved fast, accurate label detection and ingredient extraction

Created a personalized health insight engine

Designed an intuitive UI that even non-technical users can understand

Integrated AI chat to answer nutrition questions in real time

Turned a simple idea into a real working solution — thanks to Kiro AI

What we learned

How to build fast using AI-assisted development with Kiro

The importance of clean UI for data-heavy apps

How confusing traditional food labeling really is

How AI can simplify daily decisions for millions of people

The power of combining scanning, OCR, APIs, and personalized intelligence

Most importantly: A small idea becomes a real product when supported by the right tools — and Kiro played a huge role in that.

What's next for FoodSpotlight

Add meal logging and daily nutrition tracking

Add allergen alerts in real time

Improve OCR accuracy for low-light conditions

Add multilingual label interpretation

Partner with nutritionists for verified recommendations

Launch public beta on Android and iOS

FoodSpotlight is just getting started — and with Kiro AI, the roadmap becomes even more achievable.

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