# Reward System The reward system in NexaFusion is designed to incentivize significant contributions within the ecosystem, covering areas like data provision, model development, and validation, all operating within a BSC-based infrastructure. **Data Contributors**: Those who upload valuable data to the platform are rewarded with data ownership tokens, granting them ownership rights and economic benefits derived from the use of their data. **Model Developers and Tuners**: Individuals involved in developing or fine-tuning AI models receive rewards based on the usage and performance of their models. These incentives encourage ongoing development and enhancement of AI capabilities within the platform. The reward system in NexaFusion ensures that contributors are fairly compensated for their efforts in maintaining data integrity, advancing AI model development, and participating in ecosystem validation, fostering a collaborative environment for sustainable growth and innovation. --- # 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://nexa-fusion.gitbook.io/nexafusion-whitepaper-v-1.0/nexafusion-architecture/reward-system.md?ask= ``` 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.