





CyborgDB is the only Vector DB that keeps inference data end-to-end encrypted—at rest, in transit, and in-use
Instantly transform existing databases like PostgreSQL, Redis, and RDS into Confidential Vector Databases
from cyborgdb_core import Client, IndexIVFFlat
# Create a Redis-backed client
client = Client("redis", "redis://localhost")
key = secrets.token_bytes(32) # Replace with your encryption key
index = client.create_index("my_index", key, IndexIVFFlat(128, 1024))
from cyborgdb_core import Client, IndexIVFFlat
# Create a Redis-backed client
client = Client("redis", "redis://localhost")
key = secrets.token_bytes(32) # Replace with your encryption key
index = client.create_index("my_index", key, IndexIVFFlat(128, 1024))
#include "cyborgdb_core/client.hpp"
// Create a Redis-backed client
cyborg::Client client(DBConfig(cyborg::Location::kRedis, "redis://localhost"));
std::array<uint8_t, 32> key; // Replace with your encryption key
auto index = client.CreateIndex("my_index", key, cyborg::IndexIVFFlat(128, 1024));
#include "cyborgdb_core/client.hpp"
// Create a Redis-backed client
cyborg::Client client(DBConfig(cyborg::Location::kRedis, "redis://localhost"));
std::array<uint8_t, 32> key; // Replace with your encryption key
auto index = client.CreateIndex("my_index", key, cyborg::IndexIVFFlat(128, 1024));
import { Client, IndexIVFFlat } from 'cyborgdb' ;
// Connect to your own CyborgDB server
const client = new Client() ;
const key = crypto.getRandomValues(new Uint8Array(32)); // Replace with your own
const index = await client.create_index("my_index", key, IndexIVFFlat(128, 1024));
import { Client, IndexIVFFlat } from 'cyborgdb' ;
// Connect to your own CyborgDB server
const client = new Client() ;
const key = crypto.getRandomValues(new Uint8Array(32)); // Replace with your own
const index = await client.create_index("my_index", key, IndexIVFFlat(128, 1024));
import { Client, IndexIVFFlat } from 'cyborgdb' ;
// Connect to your own CyborgDB server
const client : Client = new Client("redis", "redis://localhost") ;
const key : Uint8Array = crypto.getRandomValues(new Uint8Array(32)); // Replace this
const index = await client.create_index("my_index", key, IndexIVFFlat(128, 1024));
import { Client, IndexIVFFlat } from 'cyborgdb' ;
// Connect to your own CyborgDB server
const client : Client = new Client("redis", "redis://localhost") ;
const key : Uint8Array = crypto.getRandomValues(new Uint8Array(32)); // Replace this
const index = await client.create_index("my_index", key, IndexIVFFlat(128, 1024));
curl -X POST "http://localhost:8000/v1/indexes/create" \
-H "X-API-Key: your-api-key-here" \
-d '{ "index_name":"my_index",
"index_type": "ivfpq",
"index_key": "index_key_hex" } }'
curl -X POST "http://localhost:8000/v1/indexes/create" \
-H "X-API-Key: your-api-key-here" \
-d '{ "index_name":"my_index",
"index_type": "ivfpq",
"index_key": "index_key_hex" } }'
Securely leverage similarity search for text, image, audio and more while guaranteeing privacy
Securely combine Private data retrieval with Gen.AI, enabling Confidential AI applications
Leverage Gen. AI and end-to-end encrypted vector retrieval for HIPAA-compliant RAG
Enable similarity queries on multimodal Protected Health Information in full compliance
Leverage encrypted vector search for secure multi-party fraud detection model inference
Offer personalized and context-augmented Gen. AI products while safeguarding financial data