aZen
  • About aZen
  • Introduction
  • Our Mission
  • How aZen Provides Value?
  • Home Page
  • ✨aZen Protocol
    • Introduction
    • How Does aZen Protocol Reshape Decentralized Computing?
    • Core Architecture & Key Functions
    • Application and use cases
    • Computing Architecture & Incentive Mechanism
  • ⚙️aZen Architecture
    • Overview
    • Product Overview
    • aZen DeFAI
    • SocialFi
  • 🏆aZen Hub
    • Introduction
    • Earning Center
    • Social AI Agent
    • $XaZen Pre-Mining & TGE
    • How To Get Started
    • Daily Check-in
    • Referral Rewards
    • ZenHive Rush
  • 💎aZen DePIN
    • Introduction
    • aZen DePIN Lite
  • 🖥️ZenHive
    • Introduction
    • Real-World Solution (RWS) Approach
    • ZenHive Hardware Products & Architecture
    • AI & Data Analytics Capabilities
    • ZenHive’s Target Industries
    • ZenHive’s Business Model
    • ZenHive - A Leader in DePIN AI Computing and Data Intelligence
    • ZenHive Testnet Mining
  • 💹POC Tokenomics
    • Introduction
    • $AZEN Utility
    • $AZEN Allocation
    • Proof of Contribution (PoC)
      • Token Emission
      • Proof of Contribution Categories
        • Computation PoC
        • Delegate PoC
        • Aggregate PoC
        • Data Center PoC
        • Service Delivery PoC
      • Node Operators
  • 📚Resources
    • Brand Story
    • Roadmap
    • Our Team
    • FAQ
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  1. aZen Protocol

Introduction

aZen Protocol is designed to meet this need by establishing a decentralized AI-native coordination framework, ensuring that AI computing, data, and interactions are optimized, self-governing, and economically sustainable.

At its core, aZen Protocol provides the rules, mechanisms, and incentives that enable AI agents, computing nodes, and decentralized applications (dApps) to operate in a trustless, interoperable environment.

AI-driven applications require real-time, distributed, and intelligent orchestration of resources. aZen Protocol ensures this through:

✅ Autonomous AI Task Management – AI agents execute and coordinate workloads across a decentralized computing network, optimizing performance and efficiency.

✅ Multi-Agent AI Collaboration – AI agents interact, negotiate, and execute tasks through smart contracts, enabling a self-organizing and interoperable ecosystem.

✅ Dynamic AI Governance – AI models continuously adapt to network conditions, ensuring scalability, efficiency, and economic viability.

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Last updated 2 months ago

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