CyborgDB Introduction - CyborgDB Docs

Cyborg Vector Search was renamed to CyborgDB in v0.9.0. This version of the docs will refer to the project as CyborgDB.

CyborgDB is the first Confidential Vector DB:

Introduces a novel architecture to keep confidential inference data secure through zero-trust design.
Keeps vector embeddings end-to-end encrypted throughout their lifecycle (including at search time).
Exposes a familiar API, making it easy to integrate with existing AI workflows.
Provides high-performance indexing and retrieval which can be GPU-accelerated with CUDA.
Works with DBs such as Postgres and Redis, transforming traditional DBs into Confidential Vector DBs.

Learn About CyborgDB

Learn about the architecture, design and deployment of CyborgDB.

Get started with CyborgDB and start building your first Confidential AI application.

Explore the API reference to learn how to use CyborgDB in your applications.

Cyborg Vector Search was renamed to CyborgDB in v0.9.0. This version of the docs will refer to the project as CyborgDB.

CyborgDB is the first Confidential Vector DB:

Introduces a novel architecture to keep confidential inference data secure through zero-trust design.
Keeps vector embeddings end-to-end encrypted throughout their lifecycle (including at search time).
Exposes a familiar API, making it easy to integrate with existing AI workflows.
Provides high-performance indexing and retrieval which can be GPU-accelerated with CUDA.
Works with DBs such as Postgres and Redis, transforming traditional DBs into Confidential Vector DBs.

Learn about the architecture, design and deployment of CyborgDB.

Get started with CyborgDB and start building your first Confidential AI application.

Explore the API reference to learn how to use CyborgDB in your applications.