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Liquid Domains

Unlock the value of onchain domains with a Chainlink-powered valuation price feed on the Superchain. Compatible with web2 and web3 domains, enabling minting, portfolio valuation, and smart contract integration.

Liquid Domains

Created At

Superhack 2024

Winner of

Blockscout - Use Blockscout Block Explorer!

Prize Pool

Project Description

Liquid Domains is a multichain domain name valuation service providing onchain price feeds. Users are able to manually input a domain for valuation or make an API request. This app utilizes Chainlink Functions to provide domain prices within smart contracts, unlocking liquidity for domains and enables more complex use cases such as Collateralized Debt Positions (CDPs) and loan markets.

The front end has several pages including an onchain valuation page and a mint page. The onchain valuation page allows anyone to access the API onchain and see the results. The mint page enables users to mint a multichain Liquid Domain name. The page also calculates the estimated value of each domain.

In short, this is an API endpoint powered by Chainlink to provide a price feed for web3 domains.

How it's Made

This app utilizes a Python Flask backend housing a machine learning model trained on 300k+ web2 and web3 domain sales going back to 1994. Three separate forecasting models were utilized; Ridge Regression, Random Forest, Prophet, and their results are combined to value a given domain name. Once an API endpoint was established for the model, Chainlink integrations were incorporated. Through the use of Chainlink Functions, the app is able to value a domain nft utilizing its metadata, enabling usage onchain in dApps.

The app has a front end showcasing key metrics of the dataset, latest domain valuations, and a text input for manual valuations. The API endpoint can be accessed both on and off chain, but onchain valuation is its focus.

This dataset is unique in combining web2 and web3 domains, as well as in incorporating time features enabling its context within the valuation model. The dataset is live and feeds in from a select of data sources for web3 domains, updating its dataset weekly and re-training at that time.

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