Secretarium Klave for AI

Secretarium Klave for AI is a confidential computing platform designed to enable enterprises to use AI on sensitive private data without exposing that data. It leverages Trusted Execution Environments (TEEs) to ensure data remains encrypted in memory throughout the entire AI pipeline — from ingestion and Retrieval-Augmented Generation (RAG) to inference. The platform provides cryptographic guarantees of data provenance, model lineage, and tamper-proof audit trails, enabling regulatory compliance and auditability. Private RAGs are a core component, combining an encrypted vector database, an encrypted tamper-proof governance database, and an encrypted database of mappings to securely index and retrieve private knowledge bases. AI agents can connect to multiple Private RAGs simultaneously to build collective intelligence from siloed data sources while maintaining confidentiality. The platform supports multimodal, multimodel, and multi-engine deployments including LLaMa.cpp, BitNet, and most HuggingFace models. It also features a Secure-Enclave Model Context Protocol (SMCP) that runs MCP inside secure hardware to give AI agents verifiable, auditable access to enterprise resources. Optional Raft consensus support provides a resilient, distributed ledger of interactions. The solution is designed for regulated industries such as banking, defence, and fintech, and integrates with existing TEE infrastructure and the broader Klave platform.