Core Technology Stack

To bring this vision to life, we have built a layered system that integrates AI-driven insights, real-time market data, and decentralized finance protocols. Each component, from the backend server to smart contracts and AI agents, plays a critical role in automating decision-making and optimizing trade execution. Below is a breakdown of the core technologies and how they work together to power the platform.

Backend

The backend is powered by a Node.js server that handles all API requests and coordinates between AI agents and smart contracts. It uses Web3.py for server-side blockchain operations, enabling seamless interactions with Ethereum.

Smart Contracts

Smart contracts are written in Solidity and deployed on either the Ethereum mainnet or Layer-2 networks like Arbitrum to minimize gas costs. They handle:

  • Staking and unstaking of ETH

  • Automated trading through decentralized exchanges such as Uniswap and Aave

  • Profit distribution to users

AI Agents

The AI module is built in Python and uses several key libraries:

  • Tweepy to monitor trader sentiment on X (formerly Twitter)

  • discord.py to extract signals from trading-focused Discord channels

  • NewsAPI and similar services to pull in real-time news

For analysis, we use NLP models from Hugging Face Transformers to determine the sentiment of posts and articles. An internal scoring system ranks each signal based on historical accuracy and market impact, ensuring that the most credible information drives trading decisions.

Blockchain Integration

The system is deeply integrated with Ethereum, taking advantage of its mature DeFi ecosystem. It supports:

  • Staking

  • Trade execution

  • Leveraged trading via platforms such as Aave

Data Sources

We use a combination of trusted data sources to ensure real-time awareness and accuracy:

  • X (Twitter) and Discord APIs for community sentiment

  • NewsAPI, CryptoPanic, and other feeds for market news

  • Etherscan and Chainlink for verifying blockchain transactions and tracking performance

Last updated