Cyborg

Founded 2013

Store and search encrypted vector embeddings directly within your existing database infrastructure

Pricing model

Free Tier, Paid

You can use CyborgDB to run fast vector searches across encrypted embeddings without exposing private data in memory or transit. It operates directly on top of your existing storage like PostgreSQL, Redis, or S3-compatible systems inside your private cloud or VPC. Search queries execute over ciphertext, ensuring indexing records, IDs, and metadata remain protected by keys kept exclusively in your own Key Management Service. This architecture lets you build secure retrieval-augmented generation applications, biometric matching systems, and multi-tenant AI products while maintaining strict compliance requirements.

What Cyborg does

Deploy the CyborgDB Docker container into a virtual private cloudConnect vector storage to existing PostgreSQL or S3 infrastructureGenerate and manage cryptographic keys via AWS KMSCreate encrypted vector indexes with custom dimension settingsUpsert encrypted vector embeddings and associated metadata recordsQuery ciphertext indexes using similarity distance thresholdsExport retrieval audit logs directly to cloud storage bucketsExecutes vector similarity search directly over ciphertext without decrypting the indexIntegrates with existing storage backends including PostgreSQL, Redis, and S3Maintains cryptographic tenant isolation using separate per-tenant encryption keysKeeps encryption keys strictly inside your own Key Management ServiceRuns entirely within your private cloud or on-premises environmentProtects metadata and record IDs with per-record AES-256-GCM encryptionLogs every retrieval query and per-user decryption to an audit ledger