Hubic.ai
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    • 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
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Optional Enterprise Layer

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Last updated 7 days ago

For organizations, DAOs, and institutions requiring predictable access to AI inference at scale, Hubic provides an enterprise-grade execution tier. This layer offers performance guarantees, dedicated compute pipelines, and fine-grained monetization controls — all governed by smart contracts on Ethereum.

🧾 1. Subscription-Based Access

Enterprises can subscribe to predefined packages by locking HUB tokens, unlocking:

  • Discounted inference rates based on commitment volume.

  • Guaranteed throughput even during network congestion.

  • Priority execution for business-critical inference jobs.

💳 2. Usage-Based Credit System

Instead of locking large amounts of HUB, organizations may use pay-as-you-go credits, priced dynamically based on model complexity and volume:

Mechanism
Benefit

HUB burn for access

Temporary priority queue position

Time-limited access credits

Optimize short bursts of compute or pilot deployments

Category-specific limits

Customize credit per model type (e.g. trading vs RWA)

🔐 3. Whitelisted Nodes & Private Inference

For sensitive workloads, Hubic supports the deployment of permissioned execution clusters:

Feature
Description

Custom Executor-Validator Pairs

Assign private zk-agents to internal data only

Encrypted Inference Logs

Store private outputs using zk-commitments + IPFS

Private Registries

Run isolated zkRegistry clones for NDA-bound models

These tools enable RWA asset managers, insurance firms, trading funds, or regulated DAOs to run AI in a confidential but verifiable setting — with fully enforceable on-chain monetization.

🌍 RWA Extensions:

  • Private RWA Agents: Enterprises can tokenize exclusive access to a closed-source model (e.g. via ERC-721 gating).

  • Governance-Limited Execution: Only specific wallets or DAO members can trigger agent actions.

  • Proof-Verified SLAs: zk-validated logs serve as compliance-grade execution attestations.