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Table of Contents

• Introduction
• Motivation
• Tech Stack
• Core Features
• Concepts
• Contributors

Introduction

SuperSonic is an AI-powered arbitrage and analytics platform designed to optimize trading strategies in the Web3 ecosystem. It features an AI chat agent for real-time market insights, personalized trending tokens suggestions based on social media interactions, and Twitter sentiment analysis to enhance predictive accuracy. By analyzing past DEX performance data, liquidity trends, and trading volumes, Sonic refines arbitrage strategies and forecasts high-potential tokens by combining historical data with sentiment analysis. Additionally, it supports liquid staking which enables users to maintain liquidity while contributing to network security and to maximize capital efficiency..

SuperSonic Architecture

SuperSonic is an AI-powered, cross-chain arbitrage platform on the Sonic blockchain, designed for real-time predictive trading and liquidity optimization. It integrates a data aggregation layer to fetch market data from DEXs, blockchain oracles, and social sentiment analysis powered by ZerePy AI models. The AI-driven arbitrage engine identifies pricing inefficiencies using predictive analytics and anomaly detection, ensuring profitable trade execution. Through deBridge integration, SuperSonic enables instant cross-chain arbitrage. Additionally, users can stake liquidity tokens to earn rewards, contributing to enhanced platform liquidity. Built for high-speed, automated DeFi trading, SuperSonic redefines arbitrage on Sonic with AI, staking, and cross-chain efficiency.

Motivation

The crypto ecosystem often exhibits short-lived price discrepancies across different DEXs and blockchains. Exploiting these arbitrage opportunities manually is challenging, especially considering the rapid market pace and cross-chain complexity. SuperSonic aims to automate this process using:

• Predictive AI to forecast potential price gaps,

• Sonic’s high throughput to ensure fast execution,

• deBridge integration for cross-chain liquidity movement,

• Trust-minimized smart contracts to secure user funds.

• ZerePy integration for efficient backtesting and strategy optimization

• Allora Network integration for short-term price prediction of major cryptocurrencies

• Liquidity Staking to fetch the best liquid staking yields for tokens

By streamlining the entire arbitrage lifecycle—data collection, analysis, and execution—SuperSonic helps traders capture fleeting opportunities efficiently.

Tech Stack

AI and Machine learning models:

• Python & ZerePy:
  • Automate data collection, tweet fetching, posting, and even token transfers on Sonic.
  • Integrate ZerePy’s functions to streamline AI tasks.
• Flask:
  • Serve as the backend server to orchestrate AI models, data pipelines, and API endpoints.
• Prophet Model:
  • Used for forecasting future prices based on historical data.
• Llama (LLM):
  • Fetch and analyze trending coins, leveraging its natural language capabilities.
• Sentiment Analysis:
  • Analyze tweets related to specific coins and DEX performance to inform the AI predictions.

Blockchain & Smart Contracts:

• Sonic Blockchain:
  • EVM-compatible, high-performance network for executing trades.
• deBridge:
  • Enables seamless cross-chain asset transfers.
• Solidity, Hardhat/Foundry:
  • For developing, testing, and deploying smart contracts.

Frontend:

• Next.js:
  • Framework for building a responsive, server-side rendered UI.
• Drizzle & Ethers:
  • For interacting with smart contracts on the blockchain.
• NextAuth & SWR:
  • Authentication and data fetching libraries for a smooth user experience.
• Tailwind CSS & Radix-UI:
  • For fast, customizable, and accessible UI components.
• ai-sdk:
  • For integrating additional AI-driven features directly into the frontend.

Core Features

Below is a breakdown of SuperSonic’s features, designed to optimize the entire arbitrage flow:

1. AI-Driven Prediction

Analyze on-chain data (DEX volumes, order books, liquidity) and off-chain sentiment (social media, news) to forecast imminent price discrepancies. ZerePy’s machine learning models continually refine these predictions.

2. Multi-DEX & Multi-Chain Integration

Aggregate price data from multiple DEXs (e.g., Uniswap, SushiSwap) and across different blockchains. deBridge ensures smooth token transfers between Sonic and other chains for broader arbitrage opportunities.

3. Twitter Sentiment Analysis

The Twitter Sentiment Analysis feature uses ZerePy to scrape and analyze tweets on specific coins and DEX performance, deriving sentiment scores to enhance the predictive model with real-time market trends, improving arbitrage accuracy.

4. AI-Powered Chat Agent

The AI-powered chat agent enables users to get quick responses and real-time information on any coin and the broader Web3 ecosystem. Utilizing advanced NLP models, it understands queries and fetches relevant data from blockchain analytics, exchange data, and sentiment analysis tools. By providing instant insights and trend analysis, it enhances user decision-making, making SuperSonic a powerful tool for Web3 traders and investors.

5. Personalized Trending Tokens

This feature suggests trending tokens based on the social media activity of people you follow. By analyzing influencers' interactions, it curates personalized token trends, helping users stay ahead in the Web3 ecosystem.

6. Liquid Staking

Sonic introduces liquid staking with Beets Staked Sonic (stS) and Origin Sonic (OS), allowing users to stake assets while retaining liquidity. This enhances capital efficiency by enabling participation in DeFi strategies while earning staking rewards. By integrating liquid staking, Sonic strengthens its ecosystem, driving higher user engagement, increasing protocol TVL, and fostering a more dynamic staking economy.

7. Allora Network Integration

Supports short-term price prediction of major cryptocurrencies like BTC, Ethereum, and other coins to enhance arbitrage strategies.

7. User-Friendly Dashboard

• Real-Time Analytics: View predicted arbitrage windows, potential profit, and execution status.
• Wallet Integration: Connect popular wallets (e.g., MetaMask, WalletConnect) for secure interactions.
• Trade Logs: Track historical performance and refine strategy using detailed trade histories.

Concepts

1. Predictive Modeling with ZerePy
   ZerePy’s models ingest DEX order book data, liquidity metrics, and social sentiment signals to generate probability scores for potential arbitrage. These scores inform the platform’s automated execution.

2. Cross-Chain Transfers via deBridge
   deBridge acts as the cross-chain gateway, allowing SuperSonic to seamlessly move assets between Sonic and other networks (like Ethereum, BNB Chain). This expands the scope of arbitrage beyond a single chain.

3. Liquidity Staking Tokens on Sonic
   Liquidity staking tokens on Sonic, including stS and OS, ensure efficient staking and yield optimization while maintaining flexibility and security.

Contributors

The following individuals have contributed to this project:

1. Yash Agarwal

• Role: Full Stack Developer

• Responsibilities:

1. Developing User Interface: Build an intuitive and responsive UI using Next.js and Tailwind CSS to ensure a seamless user experience.
2. State Management & Data Fetching: Utilize SWR for efficient data fetching and caching while integrating Drizzle ORM for structured database interactions.
3. Authentication & Security: Implement secure authentication using NextAuth.js to protect user data and ensure seamless login flows.
4. Blockchain Integration: Integrate Ethers.js to interact with smart contracts, enabling real-time transactions and token tracking.
5. AI & Analytics: Connect with AI-SDK to power the AI chat assistant, delivering real-time insights and market trends.

2. Mayank Rawat

• Role: UI/UX Designer
• Responsibilities:

1. User-Centered Design – Create intuitive and visually appealing interfaces that enhance user experience while ensuring seamless navigation.
2. Wireframing & Prototyping – Develop wireframes and interactive prototypes using tools like Figma to visualize user flows and interactions.
3. Consistency & Branding – Maintain a consistent design language using Radix-UI components and Tailwind CSS, ensuring a professional and cohesive look.
4. Dark & Light Mode Support – Implement a responsive theme system for accessibility and improved usability across different environments.
5. AI Chat & Dashboard UX – Design an engaging interface for the AI-powered chat assistant and interactive dashboards displaying token insights, staking details, and market trends.
6. Mobile Responsiveness – Optimize the UI for mobile and desktop devices, ensuring a smooth user experience across all screen sizes.
7. User Feedback & Iteration – Gather feedback from early users and iterate on designs to improve usability, accessibility, and overall user satisfaction.

3. Darsh Baxi

• Role: AI and ML developer
• Responsibilities:

1. Token Price Prediction – Implement forecasting models like Prophet to predict future token prices based on historical DEX performance and market trends.
2. Sentiment Analysis – Develop Twitter sentiment analysis using ZerePy, integrating social media trends into price prediction models.
3. Trending Token Detection – Use Llama (LLM) to analyze Web3 trends and identify emerging tokens based on real-time data.
4. Personalized Recommendations – Build an AI-driven system that suggests trending tokens based on users’ followed accounts and social media activity.
5. AI Chatbot Integration – Develop an AI-powered chat assistant capable of fetching real-time insights, token performance data, and Web3 ecosystem trends.
6. DEX Performance Analysis – Train ML models to analyze past DEX liquidity, trading volume, and volatility to refine price prediction accuracy.
7. Continuous Model Optimization – Fine-tune and improve AI models using real-time data, ensuring adaptability to changing market conditions.

4. Dheeraj pareek

• Role: Blockchain developer
• Responsibilities:

1. Integrates DeBridge to enable cross-chain transfers and interoperability between multiple blockchains.
2. Develops smart contracts for secure asset bridging and ensures minimal transaction latency.
3. Implements real-time liquidity tracking for seamless cross-chain arbitrage opportunities.
4. Works on optimizing gas fees and improving transaction efficiency for cross-chain operations.
5. Ensures compatibility with existing DeFi protocols, allowing users to trade and stake assets across different chains without friction.

5. Yash Kudnar

• Role: Blockchain developer
• Responsibilities:

1. Develops and implements liquid staking smart contracts for seamless token staking and unstaking.
2. Ensures security and efficiency of staking mechanisms to prevent exploits and maximize rewards.
3. Integrates stS (Beets Staked Sonic) and OS (Origin Sonic) tokens into the staking ecosystem.
4. Optimizes staking rewards distribution and APY calculations for accurate yield predictions.
5. Collaborates with the AI/ML team to provide staking insights and recommendations based on market trends.

🔗 Repository Links

Explore the core components of SuperSonic on GitHub:

• Machine Learning Algorithms
• Blockchain Backend

These repositories contain the AI-driven arbitrage models, smart contract implementations, and backend infrastructure powering SuperSonic. 🚀

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Feel free to submit an issue or contact us for feature requests or questions. We hope SuperSonic empowers you to capture profitable arbitrage opportunities with ease and efficiency. Happy trading!