GraphAI
  • Abstract
  • Unleashing the Power of Blockchain Data for AI
  • The GraphAI Manifesto
  • Core Components of GraphAI
    • Blockchain Data Indexing
    • Customizable Sub-Indexes
    • Vector Database Integration
    • Knowledge Graph Construction
    • Contextualizing Blockchain Data
    • Enhancing AI Model Understanding
  • Enhancing AI-Driven Blockchain Applications
    • Empowering LLM-Based dApps
    • Expanding Application Horizons
  • System Architecture: Scalability and Flexibility
  • Advantages of GraphAI
    • Accelerated Development of AI-Driven dApps
    • Improved AI Model Performance
    • Contextual Richness through GraphRAG
  • GraphRAG Lifecycle in GraphAI
  • Future Developments
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System Architecture: Scalability and Flexibility

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Last updated 3 months ago

GraphAI's architecture is designed to be scalable and flexible, accommodating the diverse needs of developers and the growing complexity of blockchain networks. Key features include:

  • Distributed Indexing Nodes: Ensuring efficient processing of large-scale blockchain data

  • Modular Sub-Index Creation: Allowing for customizable data structuring

  • Adaptive Vector Database Management: Optimizing storage and retrieval of high-dimensional data

  • Dynamic Knowledge Graph Updates: Continuously refining the semantic understanding of blockchain data

  • API Layer: Providing easy access to indexed data and knowledge graph for developers