QuackAI
  • 1. Quack AI Overview
    • 1.1 Introduction
    • 1.2 Why AI Governance?
    • 1.3 Vision & Objectives
  • 2. Users & Developers
    • 2.1 For Governance Participants
    • 2.2 Quack AI for Developers
    • 2.3 AI Governance Hub
  • 3. Governance Framework
    • 3.1 Proposal Processing & AI Filtering
    • 3.2 AI-Optimized Voting
    • 3.3 Treasury & Fund Allocation
    • 3.4 Governance Security & Compliance
  • 4. Quack AI Architecture
    • 4.1 AI Models & Algorithms
    • 4.2 AI Decision Making
    • 4.3 Smart Contracts & Automation
    • 4.4 Cross-Chain Infrastructure
  • 5. AI DAO Genesis Membership
    • 5.1 Overview & Utility
    • 5.2 AI Delegation & Staking
    • 5.3 Governance Rewards
  • 6. ROADMAP
    • 6.1 Future Plans
  • 7. Community
    • 7.1 Social & Community Links
  • 8. Appendices
    • 8.1 Glossary
    • 8.2 FAQs
Powered by GitBook
On this page
  1. 3. Governance Framework

3.1 Proposal Processing & AI Filtering

As the AI Snapshot, Quack AI establishes the first AI-driven governance execution framework, ensuring that proposals are not just evaluated but also autonomously enforced without manual intervention.

Governance within Quack AI follows a structured, AI-optimized decision-making process that ensures:

  • Fair and Data-Driven Proposal Evaluations -AI Agents analyze governance proposals using on-chain data, sentiment analysis, and past governance trends to assess their relevance and impact.

  • Automated Ranking & Prioritization - AI models assign priority levels to proposals based on ecosystem needs, community sentiment, and governance history.

  • AI-Orchestrated Intelligent Delegation - AI enables automated voting execution, reducing governance bottlenecks and ensuring wider participation from token holders.

Governance proposal submission follows a standardized process, where AI Agents review, analyze, and categorize proposals before they enter the voting phase. This ensures that governance remains focused on meaningful initiatives rather than spam or low-quality proposals.

AI-Driven Proposal Processing Workflow

  1. Proposal Submission: Users submit governance proposals through the AI Governance Hub.

  2. AI Initial Screening: AI Agents evaluate proposals based on historical data, governance priorities, and feasibility factors.

  3. Sentiment & Relevance Analysis: AI models scan community discussions, past governance trends, and market conditions to determine proposal significance.

  4. Automated Ranking & Categorization: AI assigns a governance priority score, ensuring critical proposals receive higher visibility.

  5. Final Review & AI Optimization: Before entering voting, AI refines proposals for clarity, accuracy, and feasibility, ensuring that only viable and impactful proposals progress.

Previous2.3 AI Governance HubNext3.2 AI-Optimized Voting

Last updated 5 days ago