Supply Mechanism And Sustainability

Unich Network is designed to maintain balance between distributing rewards to participating users and the long-term sustainability of the entire system.

Supply Adjustment Mechanism

FC supply is flexibly adjusted based on network participation levels. Although no fixed supply number is set, the system is still designed to prevent uncontrolled inflation through the following mechanisms:

• Participation-based issuance: FC is only created when users complete valuable real-world activities, such as participating in meetings, referring new users, or achieving milestones. When participation levels decrease, supply growth rate also slows down. This mechanism creates a self-regulating feedback loop: if FC becomes diluted, incentive dynamics will increase to encourage participation.

• Flexible reward adjustment: The base accumulation rate (1 FC per day) can be adjusted based on network metrics such as total active users, meeting frequency, and overall system health. If supply increases too quickly relative to adoption, the base rate can be decreased. Conversely, when the network develops stably and grows strongly, this rate can be maintained or slightly increased.

• Supply reduction mechanism: In the future, Unich Network may implement supply reduction mechanisms when users use FC to access premium services or participate in special activities. In these cases, a portion of FC will be removed from circulation, thereby reducing total supply.

Long-Term Sustainability

The advantage of the flexible supply model is that it allows the system to adapt to external environment fluctuations. When the digital asset market declines and demand decreases, supply can be adjusted to maintain value. Conversely, when adoption increases rapidly, supply can expand to distribute rewards for participation without excluding new users.

Specific details of the adjustment mechanism, including trigger thresholds and operational parameters, will be announced when Unich Network is ready for TGE. This approach allows the platform to learn from other networks' experiences, adapt to regulatory frameworks, and optimize the system to ensure long-term sustainability.