Inspiration

  1. There are already thousands of finance products on blockchains, and we don't want to just make a new finance product doing the same things as existing ones, only with different UI / name / logo. We decided to create a brand-new, eye-catching dApp.
  2. For past years, we have witnessed many dApps crashing down, because of their unhealthy token-economy. What if there exists a user-friendly tool that can help web3 solo-developer / teams to design, test, learn and spread good token economy models? What if every participant of Web3 could be able to understand, design and research tokenomics rapidly under a framework?

What it does

  1. Easy to build tokenomics model We implement a token-economy simulator engine which can be used in a low-code way. Users only need to drag some components to build up their own economy model, and then set parameters of it. Just one click on "START", everything will be calculated automatically. Also, users can stop at anytime before simulation ended, and adjust parameters. What's more, we provide data visualization panel to show what's going on during simulation.
  2. Easy to spread your tokenomics knowledge Tokenomics model built with our tool is public for free. Anyone could learn, discuss and do research on those existing models. We also consider creator economy. Research insights of models can be minted as valuable NFT! In this way, research insights can be traded on any NFT marketplace, which rewards their creators in return.

How we built it

  1. Front End We implement not only front pages, but also the entire token-economy simulator engine at front-end. Front pages include Insight NFT marketplace, creator workspace.
  2. Back End We store NFT metadata synced from on-chain events, and buy-order / sell-order, in order to improve user experience
  3. Smart Contract Currently we have ERC721, vault, marketplace contracts deployed on Polygon Testnet
  4. IPFS We put encrypted private data of NFT on IPFS so that creators on our dApp would not need to worry about their data privacy & security.

Challenges we ran into

  1. Construct a general simulation engine to adapt various token economies
  2. Update access-control of private data when NFT ownership transferred
  3. Encrypt / decrypt private data
  4. Provide easy-to-use UI

What we learned

  1. Use of Polygon's Testnet, Faucet and Polygonscan
  2. IPFS technology and application
  3. Lots of DeFi designs and their token economy
  4. Main- stream NFT marketplace design
  5. Classical encrypt / decrypt solutions

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