Proj E03-Foody

For Foodies, By Foodies

Foody is an AI Platform that’s built to provide foodies with hyper-personalised recommendations based on their personal preferences and the preferences of their community.

Introducing Proj E03-Foody

In the market of food recommendations, social media applications dominate. Yet many users are often left disappointed by food recommendations from these platforms, due to expectation differences and subjectivity in the reviews. In this project, we explored the problem statement: How might we provide tailored F&B recommendations for individuals that are accurate and objective.

Team members

Gabriel Jiaren Broughton (ESD), Dexter Leonard (CSD), Jay Edward Goh Wei Wern (DAI), Marc Yee Han Wei (ESD), Stefanie Tan Hui Zhen (CSD), Ong Zheng Han (CSD), Mubaraquali Muhammed Sufyanali (CSD)

Instructors:

  • Ying Xu

  • Cai Yutong

Writing Instructors:

  • Grace Kong

  • Dominic Quah

Project Roadmap

Background

Our main motivation for the problem was that members of our team had poor personal experiences visiting restaurants that were highly rated on traditional review platforms. This could be due to a variety of reasons such as reviews made by bots or paid biased reviews. The members of Team Foody are all passionate about the food technology space and we wanted to build our own application to deal with the lack of trustworthiness in review sites. 

It is also important to recognise the market opportunity of such an application. The rapid growth of AI technology has presented countless opportunities for disruptive innovation within the Food technology space, which was worth 34.86B USD in 2024.

Passion and opportunity are in the roots of our E-capstone project, and over the course of the past year, we’ve grown in technical capability, and we hope that the quality of the prototype does justice to the effort we’ve put into Foody.

User Validation

To validate our idea we conducted 2 exercises, here are the results and key learnings

User Survey (76 respondents):

  • Usage of food discover platforms:
    • Social media (81.58%)
    • Google reviews (72.37%)
    • Food Blogs (50%)
    • TripAdvisor (6.58%)
  • Top Reasons for Poor restaurant Experiences:
    • Expectation differences (63.04%)
    • Poor Service (32.61%)
    • Differing Taste (19.57%)

User Interviews (28 Interviewees):

  • Customers are unlikely to pay for a recommendation service, thus a B2C business model is unsustainable
  • A deeper understanding of how users interact with food discover platforms. Key decision influences for users (in descending order of importance):
    • Location
    • Cuisine
    • Pictures
    • Price
    • Written reviews
Solution

Our solution’s value proposition is that the recommendations provided are free from advertisements and paid marketing, which currently reduces the accuracy of review platforms. By using a user’s community generated reviews to generate new recommendations, recommendations are more personalised and authentic. We believe this would make the system more trustworthy, thereby solving our key problem of expectation differences and subjectivity. 

Feature Outline

In our research, we found that recommendations from a friend are more likely to be accurate, and we wanted to incorporate this idea into our solution.

Discover
Review
Dine (Coming Soon)

We developed a novel recommendation system that leverages AI to deliver hyper-personalised recommendations. For the techies out there, we used a mixture of semantic search, multi-vector search and RAG architecture to design this feature

We stripped down our review feature to only include the crucial components, as compared to other review platforms, reducing friction for users

Not only can you find new exciting places to eat, you can also reserve a table at these restaurants. We are currently prototyping a reservation feature, enabling users to go from recommendation to experience as seamlessly as possible.

Launch of our App

We launched Foody officially on the 9th of April, at Echo, an up and coming Cafe in the Central Business District (CBD) of Singapore. Over 100 early users attended. We were able to put the application in their hands, garner feedback and better understand user behaviour.

Menu

ornament-menu

Contact the Capstone Office :

+65 6499 4076

8 Somapah Road Singapore 487372

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Contact the Capstone Office :

8 Somapah Road Singapore 487372

8 Somapah Road Singapore
487372

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Contact the Capstone Office :

+65 6499 4076

8 Somapah Road Singapore 487372

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Log in to your existing account.