PalatePals

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  PalatePals - A sample interaction

Inspiration

Last holiday season, my cousin visited me from the U.K., and what was meant to be a joyous reunion turned into a challenging ordeal.

My cousin has severe dairy allergies. As we traveled across cities like New York and Dallas, we encountered the same frustrating predicament - finding vegan-friendly restaurants and navigating menu options that catered to her dietary restrictions.

It was a constant struggle to scan through endless restaurant reviews, call ahead to inquire about allergy-friendly dishes, and even resort to makeshift meal options. Despite our efforts, the online information often fell short, leaving us feeling overwhelmed and uncertain.

Witnessing my cousin's frustration firsthand, I realized there had to be a better way.

That's when the idea for PalatePals was born - an innovative solution that leverages the power of Generative AI to provide personalized meal recommendations tailored to individuals with dietary restrictions, preferences, and budget constraints.

Inspired by my cousin's journey and a passion for inclusivity, I set out to develop PalatePals, envisioning a world where everyone, regardless of dietary restrictions, could dine out with confidence and joy.

With PalatePals, individuals like my cousin can finally enjoy dining experiences that are not just safe but truly satisfying. It's not just about creating an app; it's about creating a community where everyone feels welcomed, valued, and empowered to explore the rich tapestry of global cuisine.

Join me on this journey to redefine the way we eat and unlock a world of flavor, freedom, and friendship with PalatePals. Together, let's make dining out a delightful experience for all.

What it does

The app takes user input for restaurant or cuisine choices, food allergies or other dietary preferences, and price or budget and provides dish recommendations from the restaurant menu or dishes from popular dishes from the cuisine. If the dish is not available it also provides cues to ask the chef to use different substitutes to customize and tailor the dish for enjoyment.

How we built it

The app was built using PartyRock using the widgets provided by the platform for user prompts, recommendations, and a chatbot. Claude was chosen as the LLM after experimenting with different models available on Amazon Bedrock.

Challenges we ran into

The data does not contain the latest restaurant menus available globally. We see the application evolving to include the most up-to-date information on restaurant menus.

Accomplishments that we're proud of

We are proud of our ability to transform our vision and inspiration into a tangible product, all made possible through the PartyRock platform.

What we learned

The potential of Large Language Models (LLMs) to enhance both small and significant aspects of life is profound. The current paradigm of online searches fails to capture how humans seek information and obtain answers.

What's next for PalatePals

The app will be developed as a mobile application utilizing AWS native services, ensuring seamless performance and scalability. It will be accessible through various app stores across platforms. Our revenue model will encompass a diverse range of streams, including subscription-based access, freemium features, commissions from in-app meal ordering facilitated through partnerships with meal delivery platforms, in-app advertising, and strategic collaborations with health and wellness organizations.

Built With

• amazon-web-services
• claude
• partyrock