AMORÉ EVENTS

Weddings have a huge lack of transparency at every stage of planning. We solve this by providing upfront pricing, accessibility to any ethnic group, and providing an efficient way to plan the wedding.

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Inspiration

Recently, we planned a celebratory event and were initially quoted a seemingly reasonable $2000 for the venue. However, as we delved deeper into the planning process, we encountered a myriad of additional fees that inflated the cost to $5000, should we choose to personalize our event with our own furniture, food, and decorations. This lack of transparency and flexibility posed significant challenges, particularly for those wishing to host events with a specific ethnic or niche theme.

Intrigued by this issue, we conducted interviews with three event planners and clients. The conversations illuminated a common thread of concerns: a lack of price transparency, limited availability of services and venues, and constraints on catering to specific client preferences.

These experiences and insights have fueled our inspiration for this project. Our goal is to address these challenges head-on, fostering an environment where event planning is transparent, flexible, and accommodating to the unique desires of each client.

What it does

.Our platform is an all-in-one wedding planner. It will connect you with the venues, service providers, and caterers. It will save you hours on planning. It will also provide you upfront pricing and estimations before you even talk to the vendor of the venue or service. It will also filter down all the venues in the area by filters using a dataset of information of the top search responses to wedding venues/services in the searched area.

How we built it

During brainstorming, we initially wanted to choose between a Uber Eats or LLM interface. after some time, we decided it was best to pick a more feasible to design that expressed our concept. we built the questionnaire using Typeform since reinventing a user friendly form design would take too long. we then used the responses as parameters in our model to predict the price of a venue. we relied on Streamlit community to host.

Challenges we ran into

Challenges - paying for technologies, learning curve of advanced technologies.

Accomplishments that we're proud of

.We developed an innovative algorithm that accurately predicts wedding prices based on user responses, allowing couples to plan their budgets more effectively. I’m also very proud of the way we together seamlessly as a team, we efficiently divided tasks, combining our strengths in design and coding to create a well-rounded app within the hackathon’s tight timeframe.

What we learned

We learned how to use Streamlit and deploying web apps. We learned about processing linear regression and ML models. Throughout this project, we deepened our understanding of data analysis and machine learning algorithms. We had the opportunity to work with Python libraries like Pandas and Scikit-learn.

What's next for Amore

.We see immense potential for our app beyond the hackathon. With further development and refinement, it could become a valuable tool in the wedding planning industry.

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