EVMOS blockchain Dapp that utilizes on-chain data to model potential price fluctuations in real-time from covalent api.
We combine a browser–based frontend that gives users the ability to determine price averages for any ERC20 like contract through the combination of a machine learning model and the covalent api.
Our project is an EVMOS blockchain Dapp that uses on-chain data and covalent api to model real-time price fluctuations for any ERC20 token. It provides free downloadable price prediction data in both csv and image formats, and a browser-based frontend to show users the average price for any token.
The frontend of our dapp is intuitive and easy to use. It allows users to enter the address of any ERC20 token and instantly see the average price of the token over the past 24 hours. This data is generated by our machine learning model, which uses covalent api to access on-chain data and model potential price fluctuations.
Users also have the option to download price prediction data in both text based csv format and image based png and svg. This data can be used for further analysis or to track the performance of any token over time.
Our goal is to continue to refine and improve the accuracy of our price prediction model and build out additional features to make price prediction easier and more accessible to users. We also plan to explore collaborations with other data and analytics providers to extend our reach and the utility of our application.
Developed as part of Algovera Grant
Dspytai is the first Uniswap powered Dapp that utilizes on-chain data to model potential price fluctuations in real-time.
We combine a browser–based frontend that gives users the ability to determine price averages for any ERC20 contract through the combination of a machine learning model and the Graph.
Dspytai also offers simple, free to use downloadable price prediction data in both text based csv format and image based png and svg formats that are extendable to an NFT.