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CyborgDB Embedded provides a native Python library, enabling you to integrate confidential vector search directly into your applications. This deployment model gives you maximum control, performance, and security by running entirely within your infrastructure.

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Why Choose CyborgDB Embedded?

Maximum Security
Your data never leaves your environment. Vector embeddings remain encrypted on your hardware with keys under your complete control. Ultimate Performance
Direct integration eliminates network overhead and serialization costs. Take advantage of local CPU/GPU resources and custom optimizations. Full Control
Configure every aspect of the system - from index parameters to memory management. Perfect for custom requirements and specialized deployments. Any Environment
Deploy in air-gapped networks, edge devices, or custom infrastructure where external APIs aren’t suitable. Air-gapped use requires running without an API key (free tier).

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Quick Start

Embedded Quickstart

Get running in 5 minutes with PythonStep-by-step guide covering embedded library setup and usage.
Free API Key Users: If you’re using a free API key, CyborgDB Embedded will be limited to 1,000,000 items per index.Upgrade to a paid plan to remove this limitation.

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Architecture Overview

CyborgDB Embedded integrates directly into your application process: Key Benefits:
  • No external API dependencies without an API key
  • Sub-millisecond query latency potential
  • Complete data sovereignty
  • Custom integration possibilities

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When to Use Embedded vs Service

  • Data must stay on-premises - Regulatory or security requirements
  • Ultra-low latency needed - Sub-millisecond response requirements
  • Custom integration required - Unique workflow or system requirements
  • Cost optimization critical - High-volume usage with cost sensitivity
  • Air-gapped deployment - No external network access available (free tier without an API key)
  • Single application focus - One primary application using vector search

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Next Steps

Start Building

Get hands-on with the quickstart guideFollow our comprehensive guide covering Python setup

Browse Capabilities

Explore detailed integration examplesLearn about encrypted index operations and data management

Framework Integration

LangChain and other integrationsDrop-in replacement for existing vector stores
Ready to build confidential AI applications with complete control? Start with our Embedded Quickstart guide!