Fortinet announced the availability of FortiAIGate on the Equinix Distributed AI Hub, a new validated reference architecture, giving organizations a simpler way to secure and govern AI as models, data, compute, applications, and agents become increasingly distributed. By embedding security and policy enforcement directly into AI infrastructure, organizations scale AI securely while protecting sensitive data, supporting sovereignty requirements, and maintaining visibility and control.
“Enterprise AI is quickly moving beyond isolated applications to distributed environments where models, agents, data, and infrastructure span clouds and geographies,” said Anthony James, Executive Vice President of Marketing at Fortinet. “Security needs to be built into that architecture from the start. By bringing FortiAIGate to the Equinix Distributed AI Hub, we are giving customers a simple way to secure AI interactions, protect sensitive data, maintain control over where that data is processed, and scale AI with confidence.”
Built-in Security for Distributed AI
As organizations move from experimentation to enterprise-wide AI adoption, workloads increasingly span clouds, data centers, edge environments, models, and data sources. This creates new challenges around governance, data protection, regional requirements, and performance.
The Equinix Distributed AI Hub connects AI agents, models, data, compute, and cloud providers through private, high-bandwidth, low-latency interconnection. The validated reference architecture with Equinix demonstrates how FortiAIGate can inspect AI traffic, enforce security policies, protect sensitive data, and provide visibility into AI usage within this environment. FortiAIGate has been validated as an AI security guardrail in the Equinix Distributed AI Hub, applying security closer to where AI workloads and data reside while maintaining consistent protection as deployments scale.
“AI isn’t centralized, which means enterprises need security that extends across every environment,” said Maryam Zand, Vice President, Partnerships & Ecosystem Development at Equinix. “Enterprises need to connect models, data, and clouds while retaining control over their architecture and security choices. Our distributed AI hub brings those resources together through private interconnection. The validated architecture with Fortinet gives customers a way to apply FortiAIGate security and governance to AI interactions across that connected environment.”
Secure and Scale AI without Adding Operational Complexity
FortiAIGate on the Equinix Distributed AI Hub gives organizations the security, governance, and visibility needed to move AI initiatives into production and scale them across distributed environments. Key benefits include:
- Govern AI interactions with consistent controls: Low-latency guardrails inspect prompts and responses in both directions and apply centralized security policies across sanctioned LLM and MCP traffic, delivering full control without slowing teams down.
- Control AI costs: Track per-token LLM costs and set budgets with limits and alerts, giving organizations greater control over AI consumption as adoption grows.
- Protect sensitive data and support AI sovereignty: Keep control, management, and inspection within customer infrastructure, with no data leaving the environment, to support data residency and region-specific governance requirements.
- Gain visibility across sanctioned and shadow AI: Govern approved AI interactions with FortiAIGate while FortiGate provides visibility into unsanctioned AI usage across the network.
- Maintain AI performance as security scales: Leveraging GPUs, including from NVIDIA, enables the network layer to handle security inspection with zero performance impact on AI workloads.
Consistent Protection from Network Connectivity to AI Interaction
Through the Fortinet AI-Native Security Fabric, Fortinet unifies AI security, secure networking, and infrastructure protection. Fortinet and Equinix also collaborate on network security through FortiGate VM on Equinix Network Edge.
The FortiAIGate reference architecture addresses AI traffic inspection and governance for environments built on the Equinix Distributed AI Hub. Together, they provide consistent protection from network connectivity and data movement to interactions among applications, models, agents, and users. This integrated approach enables organizations to apply security consistently and govern AI activity with greater confidence.
