AI secured by design: Encryption, Redaction & Audit controls for vector databases
Vector databases have become fundamental backbones for RAG systems, semantic search, and AI agents. They store: embeddings, reasoning traces, context windows, and real-time memories—data much more sensitive than most organizations understand and realize. However, compared to OLTP and other analytical systems, such vector stores frequently comprise the least governed, least encrypted, and least trustworthy part […]