NumNum

Inspiration

Ever felt SUPER hungry but just didn't know where to eat? Overwhelmed by all the decisions of where you could possibly eat? At NumNum, our inspiration stems from the desire to simplify this decision-making process. We created a platform that combines personalization, convenience, and discovery, offering an intuitive way to help individuals and groups find the perfect dining option without the stress of choice overload.

What it does

NumNum is a smart dining companion that:

Recommends restaurants based on user preferences, location, and mood.
Suggests dishes using AI-powered analysis of restaurant menus and user cravings.
Allows for group decision-making with AI-powered consensus on shared preferences.
Offers dietary filters (vegan, gluten-free, etc.) and allergy-conscious suggestions.

How we built it

Frontend:

Technologies: React, Next.js, Typescript

The frontend was developed using React, Next.js and TypeScript to provide a modern, scalable, and intuitive user interface. The user experience was made interactive with smooth transitions between swiping actions, search filters, and recommendation features, ensuring a delightful and seamless interface for users browsing through restaurant suggestions.

Backend:

Technologies: Flask

Flask was used to build a lightweight backend that manages AI data processing and handles the flow of restaurant recommendations. It integrates with external APIs and ensures smooth data handling for the AI models to deliver personalized suggestions to users.

API:

Technologies: Google API, Gemini API

For restaurant data fetching, we integrated the Google API to provide a real-time set of restaurant options, including details such as location, type of cuisine, ratings, and user reviews, which enhance the recommendation experience. The backend ensures secure API calls and optimizes the flow of this data to the frontend, including dynamic filtering based on user preferences and location.

We used the Gemini API to power the AI component, enabling personalized restaurant recommendations through data processing and allowing for user assistance including reservation booking, routes, and meal suggestions.

Challenges we ran into

Participating in our first hackathon has been both a rewarding and challenging experience. Along the way, we encountered hurdles such as:

Version Control: Dealing with GitHub branches and merge conflicts taught us a lot about teamwork and how to stay on the same page.
Debugging and Troubleshooting: Fixing unexpected bugs and figuring out technical hiccups tested our patience, but it also gave us some satisfying "aha!" moments.
API Integration: Getting Google Maps and the Gemini chatbot to play nicely together was a challenge, but it was super rewarding to see everything finally click!

Accomplishments that we're proud of

We were successfully able to build a functional prototype within the hackathon timeframe.
Created an intuitive and engaging UI that enhances the user experience.
Implemented an AI-driven chatbot for personalized dining assistance, our first chatbot project! Fostered collaboration and growth among a diverse team, leveraging each other's strengths to solve problems.

What we learned

Team Collaboration is Key: Working with teammates from diverse backgrounds brought fresh perspectives and ideas.
Time Management: We learned how to prioritize tasks, delegate effectively, and make impactful progress within tight deadlines.

What's next for NumNum

We believe NumNum has the potential to scale globally, beginning in urban areas and expanding to international cities where dining decisions are a common challenge. With the global food tech market projected to reach $350 billion by 2030, we believe that NumNum is able to make a lasting impact on the food-loving community. In the future, we envision integrating with food delivery apps and more to provide an all-in-one convenient dining experience.