Currently, most DAO and on-chain asset management protocols have quite simple and crude governance models—just proposals, voting, and done. But here’s the problem: the quality of data used for voting varies greatly, and after decision execution, no one tracks the actual outcomes. As a result, governance becomes increasingly inefficient, sometimes even falling into a vicious cycle of "garbage in, garbage out."

In fact, the role of oracles goes far beyond what everyone imagines. They are not just data providers but are gradually evolving into the core infrastructure of on-chain governance, capable of actively participating in and strengthening the entire decision-making process.

Let’s look at a real scenario. Suppose a DAO treasury managing hundreds of millions of dollars faces a proposal involving portfolio adjustments. What does the normal process look like? The community votes in an environment of information asymmetry—most people don’t really understand how the risk profile changes after the adjustment. But what if it’s connected to a verifiable data layer?

Before the proposal, the community can directly call this system to simulate the actual impact of the adjustment based on full-chain historical data—how the returns change, where the risk ceiling is—and finally receive an analysis report signed with node consensus. This provides factual basis for voting, rather than guesswork.

After the proposal passes, the system automatically monitors the execution process. Did the entrusted manager or smart contract strictly follow the voting decision? Are the asset allocation ratios correct? Is the risk within limits? If there’s any deviation, an immediate warning is issued.

After some time of execution, an independent performance audit report is generated. The actual effectiveness of the decision is crystal clear. Subsequent evaluation of fund managers or contributors’ performance, planning the next investment steps—all are supported by data.

This creates a complete governance closed loop—from data-driven decision-making with trusted data, to process monitoring, and then to result verification. Traditional voting transforms into truly data-driven intelligent governance.