VAST Data launches DataEnclave to allow leading AI models to run securely on sensitive enterprise data using hardware-enforced confidential computing
VAST Data has announced VAST DataEnclave, which it calls “the confidential AI capability of the VAST DataEngine”.
The capability works by enabling deployment inside customer data centres or trusted cloud hardware, including environments where leading AI models could not previously operate.
Working in collaboration with NVIDIA and other partners, VAST Data’s solution is aimed at bringing proprietary and open AI models across a range of modalities to sensitive data.
“Models are becoming a resource the operating system has to manage, the same way it manages data,” says Renen Hallak, Founder & CEO of VAST Data.
“That means knowing which model fits which task, what it can see, who can use it and under what rules, and doing all of that inside the same security and operational boundaries an enterprise applies to everything else.
“Bringing leading AI models securely to the world’s most sensitive data is where this starts. Where it leads is a world where every organisation is managing an ecosystem of fine-tuned models that represent its true intellectual property. The VAST AI Operating System is what keeps them secure, governed and useful.”
According to McKinsey, more than 80% of global organisations have deployed gen AI or agentic AI in at least one business function, and adoption is accelerating.
But in the financial industry, less than 30% of European banks have integrated gen AI and agentic AI models in their model risk management frameworks, according to the McKinsey EMEA Model Risk Management Survey.
Across financial services, healthcare, government and other highly regulated industries, some of the world’s most valuable data remains inside tightly controlled environments where moving it to an external AI service is impractical or prohibited.
That creates a fundamental challenge for AI: sensitive data often cannot move to where leading models run, while model builders cannot distribute proprietary models into infrastructure they do not trust.
Justin Boitano, Vice President of Enterprise AI at NVIDIA, says: “Enterprise data is essential to accurate, usable AI – and keeping business data confidential is critical to protecting IP in the age of agents.