TensorScan AI Whitepaper
  • 📊Executive Summary
  • 🌎Introduction
  • Project Overview
    • 🚀Project Overview
    • ⚙️Utilizing Bittensor for Decentralized Computing Power
    • 🤖AI-Driven Wallet Analysis
    • 🌐Browser Extension and Etherscan Integration
  • Tokenomics
    • 💰TensorScan AI Tokenomics
  • AI-Driven Wallet Analysis Architecture
    • 🤖AI-Driven Wallet Analysis Architecture
    • 🔄Data Ingestion and Preprocessing Module
    • 🛠️Feature Engineering and Dataset Preparation
    • 🤖Machine Learning Models
    • ⚙️Decentralized Computation with Bittensor
    • 🌐User Interface and Integration
  • Target Audience
    • 🎯Target Audience
    • 💼Casual and Serious Investors
    • 🔎Crypto Analysts and Researchers
    • 📶Traders
    • 👩‍💻Blockchain Developers
    • 🦍DeFi and NFT Communities
  • Challenges and Solutions
    • ⚙️Challenges and Solutions
    • 💻Challenge 1: High Computational Demand
    • 🔄Challenge 2: Dynamic and Evolving Data
    • 🚀Challenge 3: User Accessibility and Engagement
  • 🗺️Roadmap
Powered by GitBook
On this page
  1. Target Audience

Traders

Day traders and long-term traders alike require detailed information about the market and its participants to strategize effectively. TensorScan AI's insights into wallet categories like Diamond Hands, Snipers, or Bots help traders adapt their approaches based on the prevailing holder profiles of specific tokens.

PreviousCrypto Analysts and ResearchersNextBlockchain Developers

Last updated 1 year ago

📶