Cyborg Partners with Austin Artificial Intelligence to Deliver End-to-End Secure AI in Production

Cyborg, the pioneer enabling organizations to build and scale high-performance AI systems without compromising security, today announced a new partnership with Austin Artificial Intelligence to secure end-to-end AI infrastructure in its customer deployments. The partnership allows Austin Artificial Intelligence to deliver production-ready secure AI to market through the use of Cyborg’s flagship product, CyborgDB.

CyborgDB is the end-to-end-encrypted vector database purpose-built for regulated industries, allowing organizations to build and scale high-performance AI systems without compromising security or compliance. Built for real-world AI, CyborgDB possesses sub-millisecond latency for searching hundreds of millions of vectors without exposing a single byte of plaintext.

Security organizations like OWASP have warned that vectors and embeddings represent a fast-emerging area of vulnerability, while Fortune Business Insights predicts that the vector database market will grow to nearly $18 billion by 2034. This partnership underscores a broader industry shift in focus from AI that works to AI that works securely in production.

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“AI adoption is accelerating, but security has lagged behind,” said Nico Dupont, Founder and CEO of Cyborg. “This partnership with Austin AI shows that secure, production-ready AI infrastructure is not just possible – it’s already being deployed.”

Austin Artificial Intelligence is widely recognized as a leading consultancy, partnering with organizations to embed AI across strategy, operations, and decision-making. This partnership reduces the friction caused between AI moving into production and security being a productivity inhibitor, embracing secure AI as the industry standard.

“Our customers want to deploy AI on sensitive data without introducing new risk,” said Robert Corwin, CEO of Austin Artificial Intelligence. “Partnering with Cyborg allows us to confidently bring end-to-end security into production AI systems, giving enterprises the confidence to move faster and scale AI safely.”

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