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
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