The drive to centralize enterprise knowledge into AI models introduces significant data security challenges, as consolidated vector databases can become a high-value target for breaches. Addressing this critical need, Cyborg has introduced its Secure Enterprise RAG Blueprint, now available on the NVIDIA AI platform. This solution integrates full encryption-in-use with NVIDIA's accelerated computing stack, enabling organizations to deploy powerful retrieval-augmented generation (RAG) applications without exposing sensitive data.
Cyborg released a Secure Enterprise RAG Blueprint on build.nvidia.com and GitHub.
It provides full encryption-in-use, protecting data even during processing and queries.
The blueprint integrates with the NVIDIA AI stack, including NeMo Retriever and Nemotron models.
It addresses OWASP warnings about vulnerabilities in traditional vector databases.
Enterprises maintain full control and ownership of their encryption keys.
The solution is production-ready, supporting multimodal data and sub-10ms query performance.
Traditional vector databases leave a security gap by processing queries in plaintext, creating risks of exposure in memory, logs, or caches. The Cyborg blueprint tackles this by ensuring plaintext never exists during the search process. This approach of encryption-in-use means that vectors, metadata, and keys remain encrypted at every stage—at rest, in transit, and crucially, during use. This directly counters emerging threats identified by security organizations, allowing enterprises to innovate with AI without turning their knowledge base into a liability.
The blueprint provides a detailed, enterprise-ready architecture. The process begins with embedding generation using NVIDIA NeMo Retriever models, which are then cryptographically indexed by CyborgDB into encrypted tokens for storage. At query time, prompts are also encrypted, and retrieval is performed securely. The system leverages NVIDIA NIM microservices and NVIDIA cuVS for GPU-accelerated search, ensuring that the robust security does not compromise on performance, achieving sub-10ms query times even with encryption fully active.
The introduction of the Cyborg Enterprise RAG Blueprint represents a significant leap forward for secure AI deployment. By combining the performance of the NVIDIA AI stack with a fundamentally more secure architecture, it provides a clear path for businesses to harness the power of their data while maintaining the highest standards of privacy and compliance, effectively future-proofing their AI initiatives against evolving cyber threats.
Cyborg is pioneering a world where digital privacy is a foundational pillar of enterprise AI. Its flagship product, CyborgDB, is the first and only vector database proxy that delivers full encryption in use, ensuring vectors, metadata and keys remain encrypted at every stage. Designed for compatibility with existing databases, CyborgDB enables organizations to build and scale high-performance AI systems without compromising security or compliance. Guided by its mission to protect digital rights and data safety, Cyborg is unlocking the power of secure AI.
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