SpiceSpy

Splash screen
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Suggested recipe
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suggestions screen

Inspiration

I was tired of missing ingredients and last-minute store runs. SpiceSpy was inspired by the everyday struggle of cooking with what you have, simplifying meal prep for everyone.

What it does

SpiceSpy identifies available kitchen ingredients through photos, utilizes AI to identify ingredients and suggest recipes, and helps you create delicious meals without extra grocery trips.

How we built it

We developed SpiceSpy during a hackathon using FlutterFlow, Microsoft Azure, and Python Flask API, focusing on AI-driven ingredient recognition and recipe suggestions.

Challenges we ran into

Integrating diverse technologies, ensuring accurate ingredient recognition, and creating a user-friendly interface were significant challenges we tackled. One of the biggest challenges was prompt engineering. It took a couple of hours of trial and error cycles until we managed to fix it the way we wanted the data returned and formatted. We had to dismiss many good ideas, like real links to recipes and good images returned from recipe sites.

Accomplishments that we're proud of

Our key achievements include building a functional MVP in just 54 hours, gaining early interest from over 80 users, and seamlessly integrating advanced AI technologies.

What we learned

We deepened our understanding of AI capabilities, improved our skills in cross-platform development, and learned the importance of user feedback in app development.

What's next for SpiceSpy

Enhancing AI accuracy, expanding our recipe database with collaborations with established recipe online databases suck as supercook.com, and incorporating user feedback to refine the app and prepare for a broader market launch.