an privacy preserving recommendation service and infrastructure for the future of web3 based advertisement .
Currently most web3 platforms are in progress of decentralising their storage and hosting stack thanks to the innovative protocols and verticals defined in the space, but still advertisement and finding the web3 based profiles still need to be imperatively tracked with their web2 based metadata tracking (using obviously traditional CRM's like hubspot , even poses UX issues in GDPR jurisdictions ) in order to provide them recommendations of their potential users . Our plan is to build the privacy preserving (no cookies based tracing ) , machine learning based cross browser extension that tracks natively in browser the access pattern of their web3 sites , and based on the personal preferences (users access to which defi /NFT marketplaces / web3 app) , compares the obfuscated version of their data to find other web3 degens of their liking , while keeping their experience cluttered free, away from the dugeons of crypto-twitter ;) . similarly our main proposition for business model (for web3 companies ) is to provide an holistic analysis services based on privacy (TODO).
How it's made
this uses the following framework : - parcel 2 : for building cross native browser extension based on zero config - scaffold-eth : for making website and onbaording page for the users , also if time permits an listing of their topics on which they want to access onchain similar address / ENS based profiles. - tensorflow.js : open source framework for building the application based on the the smart contracts will be hosted on polygon.