Gaps in Current Revenue Sharing Models

While some Web3 projects and traditional platforms offer revenue-sharing mechanisms, they suffer from several limitations:

Lack of transparency: Revenue flows are often opaque, with little visibility into how funds are generated and distributed.
Centralized control: Platform owners or a small set of stakeholders retain most of the value, while contributors and users receive minimal rewards.
Limited scalability: Many models rely on manual or semi-automated processes that cannot scale with the dynamic nature of AI-driven services.
Fragmented AI integration: AI agents are often integrated as siloed tools without a unified framework for revenue generation and distribution.

There is a clear need for a next-generation revenue sharing model that is:

Last updated 7 days ago

While some Web3 projects and traditional platforms offer revenue-sharing mechanisms, they suffer from several limitations:

Lack of transparency: Revenue flows are often opaque, with little visibility into how funds are generated and distributed.
Centralized control: Platform owners or a small set of stakeholders retain most of the value, while contributors and users receive minimal rewards.
Limited scalability: Many models rely on manual or semi-automated processes that cannot scale with the dynamic nature of AI-driven services.
Fragmented AI integration: AI agents are often integrated as siloed tools without a unified framework for revenue generation and distribution.

There is a clear need for a next-generation revenue sharing model that is:

Last updated 7 days ago