Echelon AI
  • Who am I?
  • Why Echelon AI?
    • Why Echelon AI?
    • Multi-AI Agents
    • Echelon Highlights
  • Core functionality
    • Technologies Used
    • Technical Reflections
    • Echelon Core Framework
    • Use Cases
    • Tokenomics: The $Echelon Token System
    • Roadmap
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  1. Why Echelon AI?

Multi-AI Agents

PreviousWhy Echelon AI?NextEchelon Highlights

Last updated 5 months ago

Multi-AI Agents

Catcher Agent The Catcher Agent is tasked with real-time monitoring of blockchain networks and community dynamics, capturing the latest market hotspots.

Functions:

  • Extracting and interpreting transaction data on blockchains.

  • Real-time monitoring of community activities (e.g., Twitter trends, Reddit posts).

Technical Implementation:

  • Achieves millisecond-level data capture through efficient crawlers and API integrations.

Analyst Agent The Analyst Agent is the analytical core of the system, converting raw data into actionable insights.

Functions:

  • Sentiment Analysis: Analyzing the emotional inclinations within community discussions using NLP techniques.

  • Trend Prediction: Combining historical data with current dynamics to predict market directions.

Technical Implementation:

  • Emotional features of text data are mapped to predefined categories (e.g., positive, negative, neutral) using deep learning models.

  • Identifies potential investment opportunities using machine learning algorithms.

Strategist Agent The Strategist Agent is the user’s intelligent investment assistant, providing trading suggestions and assisting in execution.

Functions:

  • Strategy Generation: Offering personalized investment and stop-loss recommendations.

  • Automated Trading: Connecting to trading platforms via APIs to execute strategies automatically.

Technical Implementation:

  • Optimizes decision-making models through reinforcement learning.

  • Interfaces with decentralized exchanges (DEXs) via smart contracts.