KLEVA
Latest (Apr. 2025)
Latest (Apr. 2025)
  • Introduction to Kleva AI
    • About Kleva AI
      • Core Philosophy
      • Unlocking Hidden Value with AI
      • 3S: Simple. Secure. Saving.
  • Social & Community Links
  • Brand Kit
  • Market Context
    • Economic Context & Emerging User Needs
    • Limitations of Traditional DeFi
    • DeFAI – Solving DeFi’s Gaps with AI
  • Platform Design
    • DeFi: Conventional vs. Kleva AI’s Perspective
    • The Future of Autonomous Asset Empowerment
    • Core Systems of Kleva AI
      • 1: Autonomous Economy with Social Assets
      • 2: Referral Incentive Finance
      • 3: Onchain Incentive
  • Strategy & Business
    • Business Plan
      • Business Goals & Metrics
      • Target User Segments – Two Core Groups
  • Product Design
    • Functional Requirements
    • Product Features: Leveraging Invisible Assets
  • Technology Stack
    • Platform Architecture
      • Application & Interface Layer
      • Domain Service Layer
      • Platform Service Layer
        • Core
        • External Data Hub
        • Web3 Engine
        • Common Infra Service
      • Infra Layer
    • Key Features of Agent Runtime
      • Deployment & Model Management Framework
      • Security and Reliability Features
  • Tokenomics
    • KLEVA Token Design
      • Historical Tokenomics
      • Distribution Breakdown
  • Roadmap & Community
    • Roadmap & Timeline
      • KLEVA Protocol Era – Pre-Acquisition ('21~'24)
      • 2025–2026 Milestones
      • Community Engagement Timeline
  • Entity
  • Core Team
  • Vision
  • Commitment to the Future
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  1. Technology Stack
  2. Key Features of Agent Runtime

Deployment & Model Management Framework

Kleva AI Agent Runtime enables rapid deployment and scalable operation of multimodal AI agents through efficient resource management, MCP-compliant tools, versatile LLM/SLM packaging, and comprehensive support for prompt versioning.

  • Rapid Deployment and Scalable Infrastructure: Facilitates the swift and straightforward deployment of multimodal autonomous AI agents, offering a computing infrastructure that seamlessly scales to various sizes.​

  • Efficient Resource Sharing and Management: Provides a system for effective resource sharing and management across diverse AI services, enhancing overall operational efficiency.​

  • MCP Standard Tool Services: Offers tool services adhering to the MCP (Model-Centric Programming) standard, ensuring compatibility and ease of integration.​

  • Comprehensive LLM Support with Prompt Versioning: Supports a wide range of the latest commercial and open-source Large Language Models (LLMs), accompanied by prompt version management capabilities.​

  • Flexible AI Packaging Options: Provides various sizes of Small Language Models (SLMs) and LLM options to accommodate rational AI packaging needs, catering to different application requirements.

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Last updated 1 month ago