Modular AI Agent Design

AGENFI's intelligence backbone is built on a modular AI agent architecture, enabling flexibility, upgradability, and adaptability across use cases and evolving market conditions.

Instead of relying on a single, monolithic AI system, AGENFI deploys multiple specialized agents, each focused on a specific domain of DeFi analysis and user behavior. These agents communicate through a shared learning core, allowing for real-time cooperation and optimization.

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🧠 Core Design Principles

• Modularity: Each AI agent is independent and pluggable, allowing targeted updates and scaling.

• Specialization: Agents are trained for distinct roles (market analysis, risk, sentiment, portfolio, etc.)

• Cooperation: Agents exchange findings and reinforce accuracy through a shared inference layer.

• Continuous Learning: Live data continually refines models and strategies using reinforcement techniques.

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🧩 Agent Types in AGENFI

Agent Name	Function
📈 Market Agent	Tracks price trends, volatility, volume
💼 Portfolio Agent	Suggests asset allocation and rebalancing
⚠️ Risk Agent	Detects anomalies and risk patterns
🐋 Whale Agent	Monitors large wallet movements
💬 Sentiment Agent	Analyzes social chatter and emotional tone
🔔 Signal Agent	Triggers alerts based on AI synthesis