Trend Micro

AI Infrastructure Security 📍 Tokyo, Japan Est. 1988

Global cybersecurity company with AI-powered threat defense across cloud, endpoint, network, and AI workloads.

Headquartered in Tokyo, Japan, Trend Micro offers its Trend Vision One as a solution for organizations navigating the complexities of network-layer security and traffic inspection for AI workloads. The platform is positioned within the broader AI Infrastructure Security category, where AI Security Intelligence tracks 12 companies building specialized capabilities.

Established in 1988, Trend Micro is a mature technology company that has expanded into AI security, bringing an established customer base and enterprise credibility to this emerging category.

Why Watch This Company

Trend Micro addresses a critical gap in the AI security stack: the infrastructure layer that most AI-specific security tools take for granted. As AI workloads demand specialized compute and networking, network-layer security and traffic inspection for AI workloads becomes essential for organizations running production AI systems at scale.

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Founded
1988
📍
Headquarters
Tokyo, Japan
🛡
Category
AI Infrastructure Security
Key Product
Trend Vision One
Trend Vision One
Global cybersecurity company with AI-powered threat defense across cloud, endpoint, network, and AI workloads.
AI Infrastructure Security Landscape
AI Infrastructure Security →
AI Infrastructure Security focuses on protecting the compute, network, and platform layers that underpin AI/ML workloads. As enterprises shift AI training and inference to cloud and edge environments, the infrastructure stack — GPUs, model serving endpoints, data pipelines, API gateways, and container orchestration — becomes a high-value target. This category covers solutions that secure these components without introducing latency or limiting model performance.
12 companies tracked in this category

Key questions to evaluate any AI Infrastructure Security vendor — including Trend Micro:

Does the platform provide security controls specifically designed for GPU clusters, model serving endpoints, and AI pipeline infrastructure?
Can the solution inspect and enforce policies on AI/ML API traffic without adding significant latency to inference calls?
How does the vendor handle multi-cloud and hybrid AI deployments where workloads span different infrastructure providers?
Does the platform integrate with container orchestration and ML pipeline tools (Kubernetes, Kubeflow, MLflow)?

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Category Peers — AI Infrastructure Security

11 other companies in this category

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