Sage Union Whitepaper
  • Introduction
    • Project Overview
    • Problem Statement
    • Vision & Mission
  • Market Overview
    • Current Issues in the Information Ecosystem
    • Potential of Human-AI Collaboration
    • Competitor Analysis & Differentiation
  • SageUnion Solution
    • System Components
    • Human-AI Collaboration Model
    • Definition & Creation of High-Quality Information
  • Platform Architecture
    • Telegram Mini-App Structure
    • Data Collection & Processing Workflow
    • AI-Based Information Evaluation Mechanism
    • Reward Distribution Logic
  • Tokenomics
    • Token Overview (SAGU)
    • Token Utility & Rewards
    • Revenue Model & Sustainability
  • Governance & Community
    • User Participation Structure
    • Voting & Decision-Making Mechanism
    • Community Incentives
  • AI Learning & Quality Control
    • Data Collection Standards
    • AI Evaluation Logic
    • Continuous Learning Framework
  • Roadmap
    • Development Phases
    • Beta Launch & Official Release Timeline
    • Long-term Vision
  • Team & Partnerships
    • Team Introduction
    • Advisory Board & Partners
    • Strategic Partnerships Plan
  • Conclusion
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  1. Introduction

Problem Statement

In today's digital ecosystem, the abundance of information has paradoxically made it more difficult to access credible, high-quality knowledge. The rapid spread of misinformation, biased content, and low-effort data has led to a significant degradation in the reliability of publicly available information. Furthermore, current AI models heavily rely on vast datasets, often scraped from the internet, which may include low-quality or inaccurate information, thereby limiting the effectiveness and trustworthiness of AI-generated content.

There is a clear gap in the market for a system that can continuously collect, verify, and enhance the quality of information in collaboration with real human input—while incentivizing participants to contribute meaningful, truthful data.

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Last updated 1 month ago