Fortinet launches Secure AI Data Center to protect AI infrastructures end-to-end
Fortinet announced the Secure AI Data Center solution, an end-to-end framework purpose-built to protect AI infrastructures. Designed to secure the entire AI stack, from data center infrastructure to applications and LLMs, the solution delivers advanced AI threat defense with ultra-low latency and reduces power consumption on average by 69% compared to traditional approaches.
As part of this announcement, Fortinet introduced the FortiGate 3800G, a high-performance data center firewall that delivers the power efficiency, throughput, and scalability required for AI workloads. Powered by NP7 and SP5 ASICs and 400 GbE connectivity, the 3800G is the latest addition to the Fortinet data center firewall portfolio to deliver the hyperscale throughput, energy efficiency, and real-time GPU-cluster protection as part of the Secure AI Data Center framework.
“AI data centers demand both massive performance and deep protection,” said Nirav Shah, SVP of Products and Solutions at Fortinet. “Our Secure AI Data Center solution unifies those capabilities, combining ASIC-powered firewalls like the FortiGate 3800G with advanced protection for data, applications and LLMs so organizations can scale AI without compromising security, performance, or efficiency.”
Unified security and performance from Fortinet for AI environments
The Fortinet Secure AI Data Center solution delivers protection across the entire AI workflow, from network segmentation and encrypted traffic inspection to application and model-level defense. By embedding security at every layer, the framework helps enterprises prevent data leakage, block malicious inputs, and meet evolving AI compliance standards while maintaining the performance required for high-density GPU environments.
ASIC-accelerated segmentation and performance: Delivers hyperscale throughput while cutting energy costs per Gbps and improving data center sustainability, helping CIOs contain AI infrastructure spending without sacrificing performance.
Scalable AI infrastructure protection with Fortinet data center firewalls: Enables real-time protection of large-scale GPU clusters and AI workloads through ASIC-powered performance and 400 GbE connectivity, optimizing both security and cost efficiency across Fortinet’s high-end data center firewall portfolio.
LLM security and data protection: Protects LLMs against prompt injection, data leakage, and misuse by managing all model traffic and enforcing guardrails on inputs and outputs across local, hybrid, and public-cloud deployments.
Operational efficiency through the Fortinet Security Fabric: Unifies firewalling, application security, and AI runtime protections under one management plane, simplifying compliance, reducing audit time, and lowering operational complexity.
Granular application security for AI models and APIs: Eliminates code injection, tampering, and data theft attempts through layered defenses that inspect and sanitize all traffic before it reaches AI models.
Quantum-safe security: Embeds Post-Quantum Cryptography (PQC) and Quantum Key Distribution (QKD) to future-proof AI data confidentiality and compliance against quantum-enabled threats.
Raising the Standard for Secure, Scalable AI Data Centers
By combining these capabilities, the Secure AI Data Center solution provides a unified approach to securing GPU clusters, AI workloads, and data pipelines, enforcing zero-trust segmentation, maintaining compliance with global standards, and ensuring uninterrupted uptime for mission-critical operations.
“AI is transforming every aspect of our business, from product design to supply chain management, while introducing new operational challenges,” said Huy Ly, Head of Global IT Security, Monolithic Power Systems. “The Fortinet Secure AI Data Center solution gives us the visibility, performance, and protection we need to operate high-density GPU clusters with confidence. With this solution integrated into our AI environment, we can safeguard sensitive models and data while maintaining hyperscale throughput with greater efficiency and cost performance.”