LossEndFound

Reuniting you with what matters, faster

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Inspiration

Have you ever lost a valuable item that’s really important to you, only for it to never be seen again?

  • Over 60% of people have lost something in their lifetime.
  • In the US alone, over 400 million items are lost and found every year.
  • The average person loses up to nine items every day.

The most commonly lost items include wallets, keys, and phones. While some are lucky enough to find their lost items at home or in their car, those who lose things in public often never see them again.

The good news is that most places have a “lost and found” system, but the problem? It's manual, requiring you to reach out to someone to find out if your item has been turned in.

What it does

LossEndFound solves this problem by automating the lost and found process. It connects users who report lost items with those who find them.

  • Whether you're looking for something or reporting something found, the system uses AI-powered vector similarity search to match items based on descriptions provided by users.

How we built it

We built LossEndFound to make reconnecting lost items with their owners seamless:

  • FastAPI powers our backend for its speed and reliability.
  • Cohere embeddings capture the key features of each item.
  • ChromaDB stores and performs vector similarity searches, matching lost and found items based on cosine similarity.
  • On the frontend, we used React.js to create a user-friendly experience that makes the process quick and easy.

Challenges we ran into

As first-time hackers, we faced a few challenges:

  • Backend development was tough, especially when handling numpy array dimensions, which slowed us down during key calculations.
  • Frontend-backend integration was a challenge since it was our first time bridging these systems, making the process more complex than expected.

Accomplishments that we're proud of

We’re proud of how we pushed ourselves to learn and integrate new technologies:

  • ChromaDB, Cohere, and CORS were all new tools that we successfully implemented.
  • Overcoming these challenges showed us what’s possible when we step outside our comfort zone and collaborate effectively.

What we learned

We learned several key lessons during this project:

  • The importance of clear requirements to guide development.
  • How to navigate new technologies under pressure.
  • How to grow, adapt, and collaborate as a team to tackle complex problems.

What's next for LossEndFound

Moving forward, we plan to:

  • Add better filters for more precise searches (by date, location, and category).
  • Introduce user profiles to track lost/found items.
  • Streamline the process for reporting or updating item statuses.

These improvements will make the app even more efficient and user-friendly, keeping the focus on simplicity and effectiveness.

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