StratrosAI
  • WhitePaper of StratrosAI
    • Background
      • Introduction
      • Problem Statement
      • Industry Analysis
    • StratrosAI Introduction and Core Features
      • What is StratrosAI?
      • StratrosAI Solution
    • System Architecture and Technical Flow
      • System Architecture
      • Technical Workflow
    • DA Service API
      • gRPC Interfaces
      • ICDA Storage Canister and Confirmation Canister
        • Storage Canister
        • Confirmation Canister
    • Application and Mechanism of the Restaking Feature
      • Advantages of Restaking
      • Working Principle of Restaking
      • Infrastructure
    • Market Potential and Use Cases
      • Market Potential
      • Market Size
      • Use Cases
    • Business Model and Target Users
      • Business Model
      • Target Users
    • Costs, Challenges and Validation
      • Costs and Challenges
      • Validation
      • Open Source
    • Future Development and Competitive Comparison
      • Roadmap
      • Competitive Comparison
    • Conclusion
Powered by GitBook
On this page
  1. WhitePaper of StratrosAI
  2. Market Potential and Use Cases

Use Cases

StratrosAI provides diverse use cases, meeting the needs of core AI tasks while supporting a range of value-added services. Here are the main application scenarios:

Core Application Scenarios

  1. On-chain AI Agent Processing: StratrosAI’s DA layer and decentralized storage network provide a decentralized data storage and real-time processing environment for AI agents, enabling secure and efficient execution of AI tasks on-chain. This reliable operating environment allows intelligent tasks such as data analysis and model inference to run seamlessly on-chain.

  2. Data Preparation and Labeling: StratrosAI’s storage system provides an efficient, low-cost storage solution for AI datasets, supporting preprocessing tasks like data cleaning and labeling to ensure high-quality model training on-chain. With the DA layer’s data security and integrity guarantees, developers can focus on model building and optimization without concerns about data security.

  3. AI Projects within AVS: StratrosAI supports decentralized AI project development and operations within the AVS (AI Value System) ecosystem. Through the DA layer and restaking mechanism, developers can achieve cross-chain data sharing and efficient storage within the AVS ecosystem, creating an innovative and user-friendly incubation platform for more AI projects.

Value-added Services

  1. Content Moderation: The DA layer in StratrosAI’s AVS ecosystem enables dApps to leverage decentralized AI algorithms for content moderation and filtering, meeting global users’ needs for content safety and compliance. Decentralized moderation improves efficiency and enhances the system’s scalability and flexibility, suitable for social media and content platforms.

  2. Personal AI Assistants: StratrosAI enables users to create and manage personal AI assistants on-chain, ensuring data privacy and user control. These assistants provide personalized services through on-chain data storage and training, allowing users to view and manage their data anytime, ensuring security and privacy.

Restaking of ckBTC and ckETH: StratrosAI offers a restaking feature, allowing users to utilize ckBTC and ckETH for DA layer and network security support, delivering additional yields and enhancing the network’s decentralization and stability. Restaked assets support data processing and model computation for AI projects within the AVS ecosystem, boosting the efficiency of decentralized AI operations.

PreviousMarket SizeNextBusiness Model and Target Users

Last updated 4 months ago