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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  1. Core Components of GraphAI

Contextualizing Blockchain Data

PreviousKnowledge Graph ConstructionNextEnhancing AI Model Understanding

Last updated 5 months ago

GraphRAG allows Graphai to provide context to various types of blockchain data:

  • Transactional Data: Linking related transactions, identifying patterns, and establishing transaction chains.

  • Stateful Data: Mapping the evolution of smart contract states and account balances over time.

  • Metadata: Connecting off-chain metadata with on-chain actions for a more comprehensive view.

  • Temporal Relationships: Establishing timelines and causal relationships between blockchain events.