System Architecture

NexaFusion supports a decentralized machine learning platform through a well-structured system architecture, leveraging a BSC-based infrastructure:

Data Layer: Manages secure data upload, storage, and access, ensuring data integrity and traceability. This layer is crucial for maintaining the reliability of data used across the platform.

Model Management Interface: Facilitates the submission, management, testing, and deployment of AI models, enabling developers to work efficiently and ensuring models meet performance standards.

Reward System: Encourages contributions, from data provision to model validation, ensuring participants receive fair compensation for their efforts.

Validation/Arbitration Process: Maintains high quality and reliability of data and models, ensuring the trustworthiness and efficiency of deployed AI solutions.

By integrating these components, NexaFusion simplifies the development and deployment of AI agents while ensuring their effectiveness and reliability. This approach positions NexaFusion as a key platform for leveraging AI within the BSC-based ecosystem.