Hubic
  • 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
    • Token Flow Diagram
    • Long-Term Sustainability
    • Optional Enterprise Layer
    • Security & Reputation Systems
    • Future Expansion Points
    • Final Notes
  • 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
    • Website
    • Twitter
    • Telegram
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  1. Registry & System Architecture

Governance System

PreviousProof-of-Weights (PoW2)NextHubic Intelligence Hub (Expanded)

Last updated 4 days ago

Hubic uses a hybrid governance framework, combining token-weighted voting, activity-based reputation and zk-verifiable contributions. Governance participants can propose, vote on and enforce protocol upgrades — including the onboarding of new models, agents or RWA-linked assets.

Everything is on-chain, auditable and programmable.

🧩 Voting Power = Capital + Contribution:

HUB Token Holdings

Base voting power

Execution Uptime

Activity score for executors and agents

Inference Quality

zk-scored model accuracy and task success rate

Proposal Participation

Historical governance engagement

This blended metric ensures that both financial stake and verifiable technical contributions are represented.

🗳 Proposal Lifecycle (Struct Example):

struct Proposal {
  uint256 id;
  address proposer;
  string description;
  uint64 vote_start;
  uint64 vote_end;
  uint256 yes_votes;
  uint256 no_votes;
  bool executed;
  bytes32 model_ref; // optional zk-model reference
}

Each proposal can optionally reference a zk-model, making it possible to govern AI or RWA logic directly (e.g. adjust fees, deprecate models or update agent policies).

🧠 Advanced Governance Features:

⦿ zk-Reasoning Support:Proposals may require a zk-proof of rationale (e.g. scoring data or simulations).

⦿ Epoch-Based Voting Weight: Aligns influence with recent activity.

⦿ Model-Scoped Votes: Only stakeholders of specific models/agents can vote (ideal for RWA sub-governance).

🌍 RWA Relevance:

⦿ DAO-Controlled RWA Models: Tokenized models can be governed by holders, with fees, rewards and strategies controlled via proposals.

⦿ Royalty Configuration: Changes to payout ratios or staking thresholds can be triggered by RWA tokenholders.

⦿ Auditable Governance: Every rule, action and proposal is traceable — critical for real-world compliance and legal integration.

With Hubic, you don’t just stake on-chain — you govern real digital assets backed by computation.