Confidential vector database for secure AI workloads

Cyborg is a US-based company focused on building infrastructure for confidential and secure AI, particularly for regulated industries where data privacy, compliance, and secure inference are required. Its flagship product, CyborgDB, is a fully end-to-end encrypted vector database designed for sensitive AI workloads. The system secures data during all stages — at rest, in transit, and in use — allowing AI applications to perform similarity search, retrieval-augmented generation (RAG) and vector embeddings while preserving confidentiality.

Seamless integration with existing database and infrastructure systems (PostgreSQL, Redis, RDS) turned into secure, AI-ready index systems.

Focused use cases around confidential RAG and secure multimodal vector search, Cyborg enables organizations to apply generative AI in environments that demand high privacy and regulatory alignment. Founded by Nicolas Dupont (who is named in 14 patents on cryptography), Cyborg raised an undisclosed amount in a seed round in November 2025.