# Token System Overview

### 1. Token System Overview

#### 1) Design Philosophy — A Dual-Layer Economy that Tokenizes Data Trust

The WGA token system goes beyond a simple reward model — it is designed as an autonomous dual-token structure (Dual-Layer Token Economy) that translates data trust (Proof of Integrity) into an economic unit of value. At the core of this structure lie three pillars: the AI Proof Engine, the Soft DePIN Network, and the Token Economy.  AI verifies data (Proof), Soft DePIN distributes and preserves the results, and the token system connects these outputs into a cycle of reward, feedback, and policy control.

Accordingly, every form of participation operates within a fully circular pipe

<figure><img src="https://2341876949-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FBgwITTLE1rMrSJQdyVxT%2Fuploads%2Fn0TlYJ2zWAFi4rYaFs0K%2F2%EB%B2%88%20%EC%98%81%EC%96%B4.png?alt=media&#x26;token=fbbecf70-f1bf-4278-a614-0463f5bf764a" alt=""><figcaption></figcaption></figure>

This continuous loop forms a 3-tier trust economy integrating AI Proof + Soft DePIN + Token Economy,where all data is transformed into Proof Units (trust-based data) through AI verification — and these verified data units are, in turn, converted into real economic value.

#### 2) Dual-Token Structure — Reward Token (XYZ) vs Data Proof Token (XYZD)

The WGA economy separates Reward (XYZ) and Proof (XYZD) into distinct but interlinked mechanisms.

One functions as a utility asset driving economic circulation,while the other serves as an evidential asset that certifies data trust.

| Category  | XYZ (Utility / Reward Token)                                                           | XYZD (Data Proof Token)                                                                  |
| --------- | -------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------- |
| Role      | User rewards, payments, and campaign budget unit                                       | Data Proof asset verified and recorded by AI                                             |
| Issuance  | Hard cap of 10 billion tokens, no additional minting                                   | Automatically generated in proportion to the number of Proof data entries (non-tradable) |
| Function  | Circulation and payment focused / Deflationary through burning                         | Records activity trust levels / Serves as the basis for reward calculation               |
| Reward    | Reallocated from the Reward Pool (no additional minting)                               | Virtual reward credits issued upon successful AI verification                            |
| Burning   | Automatically burned at a set ratio during service use, campaigns, or API transactions | Discarded upon Proof expiration (not considered token burning)                           |
| Liquidity | Tradable and eligible for exchange listing                                             | Non-transferable; on-chain record only                                                   |

XYZ is the core energy driving market liquidity and reward circulation, while XYZD is the data evidence unit used by AI to assess trust. The two assets are not directly exchanged; instead, they are indirectly converted through the “Reward Credit” generated by the AI Proof Engine.

In other words, a closed loop is formed: Proof → Credit → XYZ reward → consumption and feedback. Through this structure, WGA establishes a Proof-First Economy, where no economic activity can occur without AI verification.

#### 3) Technical Foundation – Soft DePIN Logic

Traditional DePIN projects were based on sharing physical resources such as sensors, GPUs, or mobile devices, but WGA’s Soft DePIN transforms data contribution and AI verification themselves into a form of mining activity.

* **AI Policy Engine**&#x20;

: evaluates each data entry for authenticity (fraud-free) and contribution level (trust score)

* **PoE Layer (Proof-of-Engagement)**

: converts participation events into hashes and generates on-chain Proof-of-Engagement

* **Node Network**&#x20;

: performs distributed data storage and integrity verification<br>

* **WSD Reward Model (Mint-by-Integrity)**

:grants reward triggers only to AI-verified nodes

This enables a data-driven Soft Mining economy (Data Mining via Proof of Integrity) that mines trust without physical energy consumption. Web2 user activity data is also converted into Soft Node participation through SDK, API, or app integration, making user behavior itself equivalent to node contribution.

This realizes a data-based Soft Mining economy (Data Mining via Proof of Integrity) that mines trust without consuming physical energy. Web2 user behavior data is also converted into Soft Nodes through SDK, API, and app integration, making user activity itself equivalent to node participation. In other words, it is a structure where “using the app equals verification contribution (Use = Mine).”

#### 4) Dual Token Circulation Model

<figure><img src="https://2341876949-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FBgwITTLE1rMrSJQdyVxT%2Fuploads%2FVvdcJWhPuQQt63javw5t%2F3%EB%B2%88%20%EC%98%81%EC%96%B4.png?alt=media&#x26;token=300be46f-20f6-41a3-863d-cc22cf5a094f" alt=""><figcaption></figcaption></figure>

*፠  Summary of the Proof-to-Earn Cycle:*

*① Using – Advertisers deposit budgets in XYZ → on-chain campaign transactions occur*

*② Earning – User/KOL activities → AI verification → Proof generation*

*③ Conversion – Rewards calculated based on Proof reliability and paid in XYZ*

*④ Consumption – When services are paid for or data is consumed, a portion of XYZ is recirculated or burned*

*⑤ Balancing – The AI proposes policy-based adjustments to reward efficiency and distribution ratios*

<figure><img src="https://2341876949-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FBgwITTLE1rMrSJQdyVxT%2Fuploads%2FatUGDJHpLd4bzotfyPnA%2F4%EB%B2%88%20%EC%98%81%EC%96%B4.png?alt=media&#x26;token=e1fae713-1b93-404c-a06c-0ea0841be90f" alt=""><figcaption></figcaption></figure>

Through this mechanism, WGA establishes an autonomous economy where participation regulates supply and data quality is transformed into value.

<figure><img src="https://2341876949-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FBgwITTLE1rMrSJQdyVxT%2Fuploads%2FhOFj8iitVKEX1dPL6n7N%2F4%EB%B2%88%20%EC%98%81%EC%96%B4.png?alt=media&#x26;token=a71a1ceb-fa40-4470-9fd1-609dff15b414" alt=""><figcaption></figcaption></figure>

#### 5) Web2 → Web3 Soft DePIN Transition

WGA is not a Web3-exclusive system. It is designed as a Soft Node–based hybrid DePIN network that allows participation even within Web2 environments—without requiring wallets or blockchain knowledge.

* When a Web2 app or brand platform integrates the WGA SDK, user activity data from that service is automatically transmitted to the Proof Layer.
* The AI Proof Engine verifies this data and generates PoE (Proof of Engagement) records.
* The verified data is then provided to brands as a Verified Marketing Report (trust-certified SaaS report).

As a result:

① Web2 Enterprise = SoftNode Participants

② Web2 User = Indirect PoE Miner

③ Web2 data = Proof data for actual use on the WGA mainnet

<figure><img src="https://2341876949-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FBgwITTLE1rMrSJQdyVxT%2Fuploads%2F6NHbxTMuC5KvH8sZvKgU%2F4%EB%B2%88%20%EC%98%81%EC%96%B4.png?alt=media&#x26;token=a6c4c345-0477-4632-9c5c-9fb282e93e91" alt=""><figcaption></figcaption></figure>

<figure><img src="https://2341876949-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FBgwITTLE1rMrSJQdyVxT%2Fuploads%2Fn0VAsD2CrBuN6M1NFxKQ%2F1763021560(1).png?alt=media&#x26;token=d1219713-f329-45e9-8eb0-1d29110ccfe1" alt=""><figcaption></figcaption></figure>

<figure><img src="https://2341876949-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FBgwITTLE1rMrSJQdyVxT%2Fuploads%2FWxtvd3ZuXEalpgRmorne%2F1763021598(1).png?alt=media&#x26;token=678f1649-88af-4bbd-8e85-35f8a8e5f8af" alt=""><figcaption></figcaption></figure>

Through this structure, WGA naturally realizes a Cross-Domain DePIN Architecture, extending seamlessly from Web2 SaaS → Soft Node → Validator → WGA Chain (L1).

#### 6) Economic Balancing Philosophy — An AI-Regulated Self-Stabilizing Economy

The WGA economic system is not “AI-controlled” but rather designed as an AI-Assisted Policy Engine.

AI does not directly control token issuance or circulation. Instead, it evaluates data quality, participation levels, and contribution metrics to propose optimized reward efficiency and distribution ratios.

| Policy Model              | Description                                                                    | Effect                                             |
| ------------------------- | ------------------------------------------------------------------------------ | -------------------------------------------------- |
| Proof-Linked Reward       | Only AI-verified activities are eligible for rewards                           | Prevents meaningless or fraudulent participation   |
| Reward Recycling          | Unused rewards are automatically recirculated                                  | Establishes a circular economy without token burns |
| Activity-Based Allocation | Quarterly reward rates adjusted based on activity performance and data quality | Promotes a utility-driven economy                  |
| Emission Reporting        | AI generates data and reward reports, with final approval by the foundation    | Ensures transparency and market trust              |

Ultimately, WGA’s token economy functions as a Self-Balancing Proof Economy, where greater participation leads to increased trust accumulation, and higher trust results in enhanced rewards.

#### 7) Structural Differentiation — Compared to Existing DePIN and Reward Projects

| Category                   | Traditional DePIN                    | General Reward Platform          | WGA Soft DePIN                                    |
| -------------------------- | ------------------------------------ | -------------------------------- | ------------------------------------------------- |
| Resource Basis             | Physical hardware                    | Centralized server DB            | Software nodes + AI verification                  |
| Verification Entity        | Node consensus or hash power         | Admin logs / private data        | AI Proof Engine + PoE smart contracts             |
| Participation Method       | Hardware (device-based) installation | Short-term campaigns             | App usage = Soft Node participation               |
| Reward Model               | Fixed block rewards                  | Uniform reward distribution      | Differential rewards based on Proof quality       |
| Economic Policy            | Halving / manual adjustment          | Unadjusted or unlimited issuance | Automated adaptive adjustment by AI Policy Engine |
| Infrastructure Scalability | Limited                              | Closed Web2 system               | Web2 ↔ Web3 Cross Integration                     |

WGA does not require physical resources, and relies on users' trust in their data itself to fuel its economy. This is the fundamental difference between the "AI Proof-based Soft DePIN Economy."


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://web3-growth-agent.gitbook.io/wga-whitepaper-ver-1.5_en/.-tokenomics-and-incentive-architecture/token-system-overview.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
