Hubic.ai
  • Hubic AI
  • EMBARK UPON
    • Introduction
      • Proof-of-Inference (PoI)
      • Proof-of-Weights (PoWg)
      • Why Hubic?
      • Main Actors and Their Roles
      • Architecture Overview
      • Use Case Examples
      • Hubic AI Hub – Model Registry
      • RWA Integration
    • Registry & System Architecture
      • Sovereign AI Agents (On-chain AI Logic Executors)
      • Liquid Strategy Engine (LSE)
      • Proof-of-Weights (PoW2)
      • Governance System
      • Hubic Intelligence Hub (Expanded)
      • Visual System Map
    • Economic Model
      • HUB Token Utility
      • Economic Actors & Reward Mechanics
      • Token Flow Diagram
      • Long-Term Sustainability
      • Optional Enterprise Layer
      • Security & Reputation Systems
      • Summary Table
      • Future Expansion Points
      • Final Notes
    • Program Flow Overview
      • Model Registration (One-Time)
      • Inference Request (User Job)
      • Execution Phase (Off-Chain)
      • Verification Phase
      • Rewards & Settlement
      • Optional Extensions
      • Key Takeaways
    • Real-World Use Case Example
      • Introduction
      • Problem Statement
      • System Actors
      • End-to-End Flow: DAO Delegation Automation
      • Benefits to DAO Operations
      • Extensions & Advanced Use
  • Hubic Economic Engine
    • Tokenomics
    • Roadmap
  • Links
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Problem Statement

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Last updated 6 days ago

DAOs managing validator delegation on Ethereum or staking platforms face several structural challenges:

⚠️ 1. Static Logic, Manual Updates

Delegation strategies often rely on:

  • Fixed thresholds or scripts,

  • Infrequent proposal cycles,

  • Delays between metric change and action.

This leads to underperformance in dynamic markets.

⚠️ 2. Zero Auditability

AI bots (where used) are:

  • Opaque,

  • Not verifiable,

  • Impossible to trust or govern.

DAOs cannot prove that delegation logic was correct — only that it was executed.

⚠️ 3. No Monetization of Strategy

Even if an off-chain agent is accurate:

  • It earns no revenue,

  • Has no on-chain value,

  • And cannot be governed, shared, or sold.

DAOs lack the infrastructure to tokenize their intelligence.

🔍 Core Pain Points Recap:

Challenge
Description

Performance Drift

Validator uptime/APR changes rapidly — logic lags behind

Slashing Risk

Delegating to unstable validators → lost yield

Lack of Verifiability

No proof of why or how decisions were made

No Assetization Path

AI agents can't generate revenue or act as economic units

Hubic solves these gaps with zk-inference pipelines and RWA-enabled agents — where every model is verifiable, composable, and monetizable.