5. Token Model

5.1 Ecosystem Roles

xKnown's decentralized collaboration ecosystem revolves around $XKNOWN as the core engine, connecting data contributors, enterprise users, model developers, and governance participants through an incentive-aligned token system. Four primary ecosystem roles are defined:

(1) Data Contributors

• Individuals collect and upload voice data.

• Earn $XKNOWN rewards based on data quality, usage frequency, and labeling accuracy.

• Can authorize enterprises to license data for additional revenue sharing.

(2) Data Consumers (Enterprises / Developers)

• Enterprises (e.g. AI firms, corporate clients) submit data requests via DSP.

• Pay data access and task customization fees using $XKNOWN.

• Submit requests for semantic labeling, rare language collection, or multilingual training sets.

(3) DSP Node Operators

• Operate service nodes for task scheduling, data validation, and governance voting.

• Stake $XKNOWN tokens as operational collateral.

• Receive revenue shares based on contributions and governance participation.

(4) Governance Participants

• All token holders may participate in governance:

  • Propose or vote on data quality standards.

  • Decide buyback & burn parameters.

  • Vote on DSP upgrades and incentive model adjustments.

5.2 $XKNOWN Core Utilities

• Upload Incentives: Rewards for uploading and labeling tasks distributed dynamically based on data quality.

• Feature Unlocks: Unlock advanced Agent features (export formats, summarization templates, private model deployment) via $XKNOWN.

• Data Trading Medium: Enterprises use $XKNOWN to purchase data access or custom tasks.

• Platform Governance: Stake $XKNOWN to influence task priority, scoring rights, and revenue share design.

• Node Staking: DSP nodes must stake $XKNOWN to guarantee service quality.

5.3 Deflationary and Long-Term Incentive Mechanisms

(1) Buyback & Burn:

• 50% of DSP revenue used for quarterly buybacks.

• Purchased tokens sent to burn pool.

• On-chain transparency ensures sustained supply reduction.

(2) Multi-Platform Dual Incentive Model

DSP Layer integrates with multiple leading AI data marketplaces.

Cross-platform data transactions allow $XKNOWN participants to accumulate additional ecosystem incentive points alongside native platform rewards.

This architecture amplifies reward multipliers, enhances user participation yields, and fosters long-term ecosystem synergies across multiple data networks.

(3) Data Reputation and Compound Growth:

• Contributors earn Data Reputation points based on data stability, usage, and supply activeness.

• Reputation boosts data circulation weight.

• Incentivizes long-term, high-quality data contribution compounding effects.

5.4 Growth Flywheel

• AI Data Flywheel:

Contributors upload → richer datasets → Agent Optimization → rising data value → enterprises purchase → recurring $XKNOWN usage → broader user participation → better model performance → attract more enterprises

• Governance Flywheel:

Users stake → governance optimization → node activity grows → task matching & data flow improves → transaction volume rises → $XKNOWN use cases expand.

5.5 Token distribution & Vesting Plan

The total token supply is distributed as follows: 37.5% allocated to Public Sale, 12.5% to the Liquidity Pool, 15% to the Team, and 35% to Ecosystem Development. Team and Ecosystem allocations are subject to a 12-month linear vesting schedule starting from October 20, 2025, following a one-month cliff period designed to build community trust. Public Sale and Liquidity Pool allocations are fully unlocked at launch, while vesting for the remaining portions proceeds on a monthly basis.

All airdrop programs, early-stage private sales (including strategic VC rounds), incentive campaigns, and partnership grants are drawn entirely from the Ecosystem Development allocation. This structure ensures maximum long-term flexibility for platform growth, user acquisition, and strategic ecosystem expansion, while maintaining full transparency over total supply circulation.