Eleven

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Inspiration

We were inspired by boardy.ai and how it connects startup founders and other business professionals with matching counterparts. We figured the same user journey would work for finding love interests.

What it does

Eleven is a dating app designed for busy professionals who value meaningful connections without the hassle. Unlike traditional apps, Eleven skips the swiping and uses insights from a quick, casual phone call to suggest potential matches tailored to your preferences. By tapping into its extensive network, Eleven identifies individuals with shared interests and match intent. After connecting, it follows up with you for feedback, continuously fine-tuning its algorithm for even better matches. With Eleven, finding the right partner is streamlined, personalized, and efficient.

How we built it

We used Multi-Agent system using LangChain, LangGraph. For the infra, we used the Django and Next.js. Front: Next.js Backend: Django AI: LangChain + LangGraph

Challenges we ran into

The conversation API provided by elevenlabs was based on JavaScript, while our agent system was built on Django. We encountered difficulties in transferring the data provided by the user through JavaScript to our Python-based system.

Accomplishments that we're proud of

Based on the call content provided by the user, we built a system that assigns specific roles to each Multi-Agent to recommend a suitable person to the user and better listen to the user’s story.

What we learned

What's next for Eleven

In the future, we plan to search the internet for information to facilitate more natural conversations with the other party and to better introduce an ideal match.