Quack AI introduces programmable voting logic through intelligent agents, allowing governance to become automated, responsive, and user-aligned — without requiring constant input from participants.
Built-In Compliance & Identity Infrastructure
Intelligent Delegation
Users can assign their governance power to AI agents that operate based on specific logic and on-chain behavior. These agents are modular, purpose-driven, and adaptable to changing context.
Delegation preferences can be configured to:
Support proposals with a high Governance Score
Abstain from certain categories or flagged risk levels
Prioritize compliance-focused outcomes
Follow off-chain sentiment or community alignment signals
Block proposals from unknown or unverified sources
This structure removes the need for users to engage in every decision, while maintaining full transparency and control.
On-Chain Execution by Agents
Once a proposal passes the scoring and prioritization phase, agents can:
Cast votes based on their assigned logic
Trigger on-chain execution of treasury transfers, role changes, contract upgrades, or compliance actions
Log all actions with clear attribution to the originating agent and delegator
Users can override or revoke delegation at any time. Every vote and action is recorded on-chain for visibility and auditing.
Reputation-Based Delegation
To build trust and accountability, each agent maintains an on-chain profile that includes:
Historical voting behavior
Alignment with successful outcomes
Override frequency by delegators
Performance across specific proposal categories
Users can review agent history before assigning delegation, making the process measurable and performance-driven.
Benefits at Scale
Reduces voter fatigue without sacrificing trust
Enables always-on execution with minimal friction
Makes governance accessible for retail and institutional users
Builds the foundation for RWA platforms to govern at speed, without manual bottlenecks
Adds structure and reliability to governance across chains and protocols
This system is not about removing human input. It is about scaling governance to match the complexity of modern on-chain ecosystems. AI agents enable governance to move faster, stay transparent, and adapt to intent — without losing control.
