Uniswap centered Dapp that utilizes on-chain data to model potential price fluctuations in real-time.

Dspytai is the 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.

Current Technical Implementation

Dspytai is built with a combination of React Components and Flask and is hosted on Vercel and Heroku. It utilizes The Graph hosted service to query Uniswap data using Python. Due to observations of small discrepancies in data, we have focused on reliability of the data feed for the machine learning algorithm and subsequent price predictions.

GitHub mono repository: https://github.com/dspytdao/dspytai

Back End with python: https://github.com/dspytdao/Heroku_Graph_ML

Algovera Proposal: https://forum.algovera.ai/t/dspyt-ai-uniswap-portfolio-tracker/184

Advanced Realized Volatility and Quarticity Blog Post: https://dspyt.com/advanced-realized-volatility-and-quarticity