Develop systems using [[Substrate]]'s governance mechanisms to allocate and track privacy budgets across multiple queries or [[Federated Learning within the Data Marketplace|training sessions]], preventing privacy depletion over time [100]. This is critical for long-term AI applications. By managing privacy budgets, we ensure that the cumulative privacy loss from multiple queries or training iterations remains within acceptable limits, allowing the system to support ongoing AI tasks without risking overexposure of sensitive data, such as in a longitudinal study tracking patient outcomes over years while maintaining transparency through Substrate's immutable storage. See also: [[ZKP/Research/Noise/Integration with Homomorphic Encryption|Integration with Homomorphic Encryption]]