project screenshot 1
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project screenshot 4 provides massive user behavior data for developers without sacrificing users’ privacy. We are building a composable, universal user profile data layer that is high efficiency, privacy-preserving, and fits web3 paradigm.

Created At

ETHGlobal Paris

Winner of


🥇 Mask Network — Best Use of RelationService


🏃 Airstack — Runner Up


5️⃣ QuickNode — Top 5

Project Description provides massive user behavior data for developers without sacrificing users’ privacy

User behavioral data is being stolen by tech giants, recklessly used, and even sold for their own benefit, media platforms are using this data to increase user retention, advertising platforms are using this data to drive deals, and in web2, it's a $2.8B market.

Today, will take back the data from Tech giants and make it available to developers to create value without sacrificing users’ privacy. is a composable, universal user profile data layer that has the following features:

  • High efficiency - Data is a non-competitive resource that has more value if it is used more. However, web2’s data silo makes data only flow in separate tech giants. By aggregating all data into a layer makes everyone can use data to create value, which makes data more efficient.

  • Privacy-preserving - Users can control whether their data is used or not and their identity is kept completely confidential.

  • Web3 paradigm - Compared to web2’s DMP(data management platform), web3 has a new identifier other than cookies & device No., which is wallet address, and web3 data is a new goldmine for value creation. re-designed the DMP into the data layer and adopts it to web3.

  • AI enabled - All tags are generated using LLM from user's transactions, we can have massive user data just by typing in the address, without any kind of human curation.

How it's Made

For the demo, we made a simple news platform that uses our data layer for content recommendation.

Technologies used:

  • Identity:, Sismo
  • Data query: Airstack, Quick Node
  • Wallet: Wallet Connect
  • LLM: GPT-3.5 turbo
  • Others: Next.js, Vercel, MangoDB

Key components:

  • Identity aggregator Identity aggregator gathers users' accounts in different ways and provides identities for Address to tag API to analyze. Using’s relation service, we can have a user’s Socials(Twitter, Github, Discord) from his/her address and ENS, etc. Using Sismo, we can turn some data gem into tags and do not need users to connect several wallets.

  • Address to tag API Input an address, and output tags related to these addresses. Using Airstack, we can query all the transaction history for a user and we use GPT-3.5 as the LLM to tag them, with QuickNode, we get all NFT collections related to the address.

  • Content matcher & Content platform This is just a demo and shows how can be used in content recommendation scenarios. We use React, Next.js, and Wallet Connect , also, we use LLM to get tags from the content and match them with users' tags.

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