ToteDAO
ZK-proofed products reviews. Get paid as a verified user. Powered by IOME.AI and Polygon.
About
The problem it solves TL;DR: Verifiable good quality demography-specific reviews must be a basic access right to prospects, customers and product companies. This seems to be an open problem. Problem: 1. e-Commerce has been one of the largest success stories on the internet for the past few decades 2. Today’s purchase experience lacks “touch-and-feel”. Users now rely more on customer reviews 3. Companies too rely on these reviews to improvise products in their future batches/cycles 4. We’re pestered by review farms and irrelevant feedback out of context 5. Gartner, G2 et. al. have tried to fix these issues, but lack decentralizaion in their ecosystem Solution: 1. Build a DAO for genuine reviews by targeted demographic users verified by KYC-Ed ZK-proof wallet 2. PI is hidden away by the power of ZK proofs on the KYC data 3. Prospects and companies source honest reviews from specific demography they favour 4. DAO members identify themselves to a demography and provide genuine reviews for bounty/rewards Employ AI to track common keywords and bucket them into weighted sentiments
How it's made
Challenges we ran into Originally, we planned to use the following tech stack: Matic / Polygon: The easiest ledger of choice today Alchemy: Easiest guided access to Polygon Smart Contract development 10M3: Zk-proofed KYC-ed private BIP44 wallet, powered by MOI Web3.Storage: Storing review data and related datasets Spheron Protocol: To access Polygon Network Covalent API: To query Polygon Network and apply NLP on review datasets EPNS: To alert users on status of actions Arcana Network: To share product insights with companies in a permissible manner Router Protocol: Cross-chain settlements of bounties React.js: Front-end web app for DAO activities Node.js: For some middleware activities Solidity: Not-so-smart contracts, duh! We ended up only using the following due to proper tooling and support: 1. Polygon, 2. Alchemy 3. IOME on MOI, 4. Web3.storage, 5. Sentimental Analysis using NLP We could not use the following: 1. Covalent API (Our NLP model still hasn't progressed to a stage where we can use Blockchain state for sentinment analysis) 2. EPNS (Did not get enough support to setup a channel on Polygon Mumbai and had to limit scope)