Patent Filed for Secure AI Infrastructure Combining Secret Sharing AONT Technology with Retrieval Augmented Generation

This new architectural approach focuses on enhancing the security of enterprise AI systems by combining Secret Sharing technology, specifically All-Or-Nothing Transform, with Retrieval Augmented Generation. By distributing data fragments across multiple locations, the system ensures that sensitive information remains unreadable even if individual storage components are compromised. This method addresses significant security concerns regarding the handling of proprietary data within Large Language Model workflows. From a technical perspective, the implementation involves managing dependencies between the secret sharing layer and the existing RAG pipeline. Engineers must consider how data chunking and retrieval latency are affected by the encryption and fragmentation process. The proposed infrastructure aims to provide a secure environment where internal documents can be indexed and queried without exposing the full plaintext to any single point of failure. Operational deployment requires careful validation of permissions and compatibility with existing cloud or on-premise storage configurations. Teams should prioritize staging tests to measure the overhead introduced by the AONT processes before moving to a full production rollout. This phased approach allows for the isolation of potential performance bottlenecks while ensuring that the integrity of the secret sharing mechanism is maintained throughout the data lifecycle.