TrendAI, a leader in enterprise AI security, has announced a new integration with NVIDIA’s DSX Air platform, enabling organizations to design, test, and validate AI factory security before deployment rather than addressing risks after infrastructure is already live. As AI adoption accelerates across industries, this collaboration introduces a proactive, design-first approach to securing AI environments, helping enterprises reduce risk while improving deployment efficiency.

Traditionally, organizations have treated security as a post-deployment layer. However, with the growing complexity of AI-driven infrastructures, this reactive model is no longer sufficient. Therefore, TrendAI and NVIDIA are shifting the paradigm by embedding security validation directly into the early stages of AI factory design. By leveraging digital twin simulations, enterprises can now assess how security controls will perform in real-world scenarios before committing to physical infrastructure investments.

Rachel Jin, Chief Platform and Business Officer, Head of TrendAI, emphasized the importance of this shift:
“True innovation requires the best of both worlds: AI plus cybersecurity. Securing AI at scale isn’t something you can bolt on later. It requires a purpose-built foundation. By empowering customers to check the impact of security on digital twin simulations, we’re pioneering a new Secure AI Factory approach.”

At the core of this innovation is the NVIDIA DSX Air platform, a cloud-hosted network simulation environment that enables organizations to build and test digital replicas of AI data center infrastructure. As a result, businesses can significantly reduce costs, accelerate deployment timelines, and validate configurations at scale without relying on traditional lab environments. This capability not only improves efficiency but also ensures that potential vulnerabilities are identified and addressed earlier in the lifecycle.

Amit Katz, VP of Networking at NVIDIA, highlighted the strategic value of the collaboration:
“NVIDIA is focused on simplifying and accelerating the design and validation of next-generation AI factories. Working with partners like TrendAI provides organizations with the visibility to detect threats across the entire stack, from cloud to endpoint, so they can focus on scaling AI without compromising security.”

Meanwhile, the importance of securing AI systems continues to grow. According to IBM, more than 10% of global organizations experienced data breaches involving AI models or applications in the past year. Additionally, companies lacking AI-driven security and automation faced breach costs nearly $1.9 million higher than those with such capabilities. These findings underline the urgent need for integrated, proactive security strategies that address risks such as weak access controls and compromised supply chains.

To address these challenges, the integration introduces two key components. First, TrendAI Vision One AI Factory EDR provides deep visibility into AI environments through a lightweight agent deployed on NVIDIA BlueField DPUs. It monitors file activity, network interfaces, and processes while leveraging advanced threat intelligence to detect suspicious behavior. Furthermore, organizations can simulate real-world attack scenarios using red-team exercises aligned with MITRE frameworks, allowing them to test and strengthen their security posture.

Second, TrendAI TippingPoint delivers high-performance network defense by enabling organizations to evaluate virtual patching and intrusion prevention capabilities. By utilizing TrendAI’s Zero Day Initiative (ZDI) and proven IDS/IPS technologies, businesses can protect against both known and emerging threats. In addition, digital twin simulations allow teams to test patch deployment strategies safely, ensuring minimal disruption to live operations.

Ultimately, this integration empowers enterprises to adopt a “secure-by-design” approach to AI factory development. Instead of reacting to threats after deployment, organizations can proactively validate security controls, optimize infrastructure, and build resilience from the ground up. As AI continues to reshape digital ecosystems, such forward-looking strategies will be essential for maintaining trust, compliance, and operational stability.

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