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NetworX

NetworX is Zk talent matching platform to make all hiring free from discrimination

NetworX

Created At

ETHGlobal Tokyo

Winner of

🏊 Worldcoin — Pool Prize

🔟 Lens — Top 10

Project Description

NetworX is the Zk talent matching platform. We use Zk proof to verify people’s authenticity without revealing their identity. This enables the hiring process to be free from discrimination such as race, religious, sex, and age.

Issues:

People easily tend to be biased by race, religion, and age when they hire other people. The research is said that Job applicants receive 50% more responses if they hide their real names.

For this time, we decided to tackle this issue. We think that building pseudonym based professional networking service helps people to remove the biases under the recruitment process.

We made :

  1. People can find potential business partners without revealing privacy. NetworX uses Zk to store privacy info. Users can reveal personal information to only trusted people.
  2. Use On-chain data for matching algorithm. Our matching algorithm uses on-chain data. People can match based on NFT interest, similar transaction behavior, and any other on-chain credential data.
  3. Bring social relationship onto blockchain NetworX collects reviews of matched relationship. These reviews are not considered any biases.

As a result, NetworX enables all hiring free from discrimination.

How it's Made

The following are the tools used for blockchain-related features:

・Metamask:To allow users to log in with Metamask wallet. ・Worldcoin:We used Worldcoin to verify as a human. ・Huddle01: We’re using Huddle01 to start an instant meeting with wallet. You don't have to sign up and jump into a meeting with web3 talent. ・Lens protocol:Integrate for matching algorithm. We analyze Lens protocol social relationship to improve matching algorithm. ・Quicknode:We're using Quicknode to match similar interest based on NFTs data, and transaction behavior. ・Lit protocol:We used Lit protocol to store private information such as resumes, sex, name, or any other info users think personal.

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