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.
🧠 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.
🧩 Agent Types in AGENFI
📈 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
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