REVOX AI Introduction
  • ⛳Introduction
    • The Mission of REVOX AI
    • The Problem with Current AI and dApp Integration
    • The REVOX AI Solutions Overview
  • 🧩Building Blocks of REVOX AI
    • Primitive Agents
    • Plugins
    • Context Knowledge
    • REVOX AI Web Extension
    • Compound Agents and Workflows
    • Onchain AI Infernece: DPrompt
  • 📚Use Cases and Examples
    • Social Data Analysis of Real-time Cryptocurrency Price Fluctuations
    • An Intent-based Crypto Trading Bot from Users' Natural Language Prompt
  • 🎯Products
    • Made by REVOX AI
    • AI Recommendation
  • Roadmap
    • Roadmap
  • Tokenomics
    • Tokenomics
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  1. Building Blocks of REVOX AI

Context Knowledge

In the diverse and expansive world of decentralized applications, the ability of agents to navigate and perform tasks across specific domains—ranging from intricate project details in the blockchain space to specialized academic fields—relies heavily on their access to relevant, domain-specific information. Such specialized knowledge is often beyond the scope of general-purpose AI model training, necessitating a more tailored approach to information access. This is where Context Knowledge within the REVOX AI ecosystem plays a crucial role.

The Essence of Context Knowledge

REVOX AI empowers developers to imbue agents with Context Knowledge, ensuring that they are not only well-informed but also capable of adapting to the evolving landscapes of their respective domains. This knowledge base can be both static, containing fixed data points relevant to the agent's tasks, and dynamic, allowing for updates as new information becomes available or as the domain itself evolves. Through Context Knowledge, agents gain a deeper understanding of their operational context, enabling them to execute tasks with enhanced accuracy and insight.

Use Cases for Context Knowledge

  • Project Whitepapers: Agents can access and understand detailed project whitepapers, allowing them to provide users with insights into blockchain projects, technological innovations, and project roadmaps.

  • Ticker Lists: In financial applications, agents equipped with updated ticker lists can accurately identify and interact with a vast array of assets, enhancing trading strategies and market analysis.

  • SKU Lists: for E-commerce: E-commerce agents benefit from having detailed SKU lists, enabling them to assist users in navigating products, comparing options, and making informed purchasing decisions.

Integration and Accessibility

Context Knowledge is seamlessly integrated into the fabric of the REVOX AI ecosystem, accessible to agents as they perform their designated tasks. This integration ensures that agents operate not in isolation but as informed entities capable of leveraging specific, relevant information to address user needs. The dynamic nature of Context Knowledge allows for continuous adaptation, ensuring that agents remain up-to-date and effective, regardless of how rapidly a domain may evolve.

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Last updated 9 months ago

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