Malibu AI enables enterprise-grade Federated Learning (FL). Train large-scale foundation models across distributed data sources without compromising privacy, ensuring compliance with global data sovereignty regulations.
Leverage Secure Multi-Party Computation (SMPC) and Differential Privacy to ensure raw data never leaves its original silo during the aggregation phase.
Deploy optimized LLMs on the edge. Our inference engine utilizes advanced quantization and pruning techniques for low-latency predictions.
Implement an asynchronous aggregation server that handles model updates from heterogeneous clients, optimizing global model convergence rates.