## Inspiration

As college students, we both agreed that fun trips definitely make college memorable. However, we are sometimes hesitant about initiating plans because of the low probability of plans making it out of the group chat. Our biggest problem was being able to find unique but local activities to do with a big group, and that inspired the creation of PawPals.

## What it does

Based on a list of criteria, we prompt OpenAI's API to generate the perfect itinerary for your trip, breaking down hour by hour a schedule of suggestions to have an amazing trip. This relieves some of the underlying stresses of planning trips such as research and decision-making.

## How we built it

On the front-end, we utilized Figma to develop an UI design that we then translated into React.js to develop a web app. We connect a Python back-end through the utilization of Fast API to integrate the usage of SQLite and OpenAI API into our web application.

## Challenges we ran into

Some challenges we ran into were the lack of experience in Full-Stack development. We did not have the strongest technical skill sets needed; thus, we took this time to explore and learn new technologies in order to accomplish the project. Furthermore, we recognized the long time it takes for OpenAI API to generate text, leading us to in the future output the generated text as a stream utilizing the SDK for it by Vercel.

## Accomplishments that we're proud of

As a team of two, we were very proud of our final product and took pride in our work. We came up with a plan and vision that we truly dedicated ourselves to in order to accomplish it. Even though we have not had too much experience in creating a full-stack application and developing a Figma design, we decided to take the leap in exploring these domains, going out of our comfort zone which allowed us to truly learn a lot from this experience.

## What we learned

We learned the value of coming up with a plan and solving problems that arise creatively. There is always a solution to a goal, and we found that we simply need to find it. Furthermore, we both were able to develop ourselves technically as we explored new domains and technologies, pushing our knowledge to greater breadth and depth. We were also able to meet many people along the way that would provide pieces of advice and guidance on paths and technologies to look into. These people accelerated the learning process and truly added a lot to the hackathon experience. Overall, this hackathon was an amazing learning experience for us!

## What's next for PawPals

We hope to deploy the site on Vercel and develop a mobile application of the app. We believe with the streaming technology, we can create faster response time. Furthermore, through some more scaling in interconnectivity with friends, budgeting, and schedule adjusting, we will be able to create an application that will definitely shift the travel planning industry!
## Inspiration

One of our team members had prior experience working a front desk job and recognized how AI could handle most of the responsibilities of a front desk representative. Inspired by this, we decided to create a system that automates these functions, focusing specifically on a dentistry office.

## What it does

Our application, FrontDesk AI, is an AI assistant designed to perform front desk functions for a dental practice. It manages appointment scheduling for prospective patients, streamlining the booking process.

## How we built it

We developed our solution using an open-source voice assistant framework called Verbi. For natural language processing, we used the Groq large language model (LLM), and Deepgram for both text-to-speech and speech-to-text capabilities. All schedule data is stored in SingleStore, and we integrated Airflow to automate database reads and writes.

## Challenges we ran into

One of the biggest challenges we faced was handling AI hallucinations and generating accurate responses. We overcame this by integrating multiple Groq models, where the output from one model was fed into another to refine the final response.

## Accomplishments that we're proud of

We are proud of learning about the functionalities of each of our AI tools. We are also proud of developing our overall infrastructure and having everything function as it should from a system design standpoint.

## What we learned

We gained experience working with Groq, Airflow, Deepgram, and SingleStore, and learned a lot about integrating and troubleshooting connections between these technologies.

## What's next for FrontDesk AI

Our next steps include integrating phone call functionality using Twilio to extend communication capabilities. Additionally, we want to expand the application beyond just appointment scheduling through Google Calendar to include features like sending personalized notes to staff via email or phone. We also aim to improve scalability so that the application can support multiple devices (10+ devices) under the same database, enabling broader deployment across practices.
## Inspiration

Travel planning is a pain. Even after you find the places you want to visit, you still need to find out when they're open, how far away they are from one another, and work within your budget. With Wander, automatically create an itinerary based on your preferences – just pick where you want to go, and we'll handle the rest for you.

## What it does

Wander shows you the top destinations, events, and eats wherever your travels take you, with your preferences, budget, and transportation in mind. For each day of your trip, Wander creates a schedule for you with a selection of places to visit, lunch, and dinner. It plans around your meals, open hours, event times, and destination proximity to make each day run as smoothly as possible.

## How we built it

We built the backend on Node.js and Express which uses the Foursquare API to find relevant food and travel destinations and schedules the itinerary based on the event type, calculated distances, and open hours. The native iOS client is built in Swift.

## Challenges we ran into

We had a hard time finding all the event data that we wanted in one place. In addition, we found it challenging to sync the information between the backend and the client.

## Accomplishments that we're proud of

We’re really proud of our mascot, Little Bloop, and the overall design of our app – we worked hard to make the user experience as smooth as possible. We’re also proud of the way our team worked together (even in the early hours of the morning!), and we really believe that Wander can change the way we travel.

## What we learned

It was surprising to discover that there were so many ways to build off of our original idea for Wander and make it more useful for travelers. After laying the technical foundation for Wander, we kept brainstorming new ways that we could make the itinerary scheduler even more useful, and thinking of more that we could account for – for instance, how open hours of venues could affect the itinerary. We also learned a lot about the importance of design and finding the best user flow in the context of traveling and being mobile.

## What's next for Wander

We would love to continue working on Wander, iterating on the user flow to craft the friendliest end experience while optimizing the algorithms for creating itineraries and generating better destination suggestions.