AIX Protocol
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  • ⭐Welcome to the AIX Protocol
  • ⭐Why We Build This?
  • ⭐Goal & Vision
  • AI Virtual Machine (AVM)
    • About The Product
    • Key Features
    • Architecture
    • Use Cases
    • Future Development
  • Decentralized AI Marketplace
    • About The Product
    • USP & Use Cases
    • Stand Out Features
    • Benefits of the Product
    • Future Development
  • AI Model & AI Agent Hosting
    • About The Product
    • What the Product Can Offer
    • Benefits of the Product
    • Use Cases
    • Integration with AIX Ecosystem
    • Future Development
  • AI Node
    • About The Product
    • Offerings & Benefits
    • Quick Guideline
    • Main Features
  • AI Agents Launchpad
    • About The Product
    • Key Features
    • Workflow
  • AIX Analytics
    • The Automated AI Analysis Tool
    • Key Features
    • Workflow
    • Use Cases
    • Technical Components
  • AI Swarm System
    • About The Product
    • Key Features
    • Workflow
    • Use Cases
  • AI Publisher
    • About The Product
    • Main Features
  • DeFAI Supporter
    • About The Product
    • Core Components
    • Support Mechanisms
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  1. AI Agents Launchpad

Workflow

Step 1: AI Agent Creation

  • Start with pre-built templates or create custom AI workflows using the IDE or drag-and-drop builder.

  • Train models using local or distributed resources on the AIX Network.

Step 2: Testing and Validation

  • Use sandbox environments to test AI agents.

  • Validate performance metrics such as accuracy, latency, and resource consumption.

Step 3: Deployment

  • Deploy agents to the AIX Network via one-click deployment.

  • Configure scalability and redundancy settings.

Step 4: Marketplace Integration

  • List agents on the AI Agent Marketplace for monetization.

  • Set pricing models, including pay-per-use or subscription-based plans.

Step 5: Monitoring and Updates

  • Monitor agent performance in real-time.

  • Roll out updates seamlessly using the CI/CD pipeline.

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Last updated 3 months ago