F convergence of networking and security, has announced the
SECURE AI DATA CENTRE
Fortinet launches secure AI Data Centre Solution to protect models, data and infrastructure at scale
ortinet, a global cybersecurity leader driving the
F convergence of networking and security, has announced the
Secure AI Data Centre solution, the industry’ s first end-toend framework purpose-built to protect AI infrastructures.
Designed to secure the full AI stack, from data centre infrastructure to applications and large language models( LLMs), the solution delivers advanced AI threat defence with ultra-low latency and reduces power consumption on average by 69 % compared with traditional approaches.
As part of this announcement, Fortinet introduced the FortiGate 3800G, a high-performance data centre 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 centre firewall portfolio to deliver the hyperscale throughput, energy efficiency and real-time GPU-cluster protection as part of the Secure AI Data Centre framework.
“ AI data centres demand both massive performance and deep protection,” said Nirav Shah, Senior Vice President of Products and Solutions at Fortinet.“ Our Secure AI Data Centre solution unifies those capabilities, combining ASIC-powered firewalls like the FortiGate 3800G with advanced protection for data, applications and LLMs so organisations can scale AI without compromising security, performance or efficiency.”
Unified security and performance from Fortinet for modern AI environments
The Fortinet Secure AI Data Centre solution delivers comprehensive protection across the entire AI workflow, from network segmentation and encrypted traffic inspection to application and model-level defence. 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 centre sustainability, helping CIOs contain AI infrastructure spending without sacrificing performance.
• Scalable AI infrastructure protection with Fortinet data centre firewalls: Enables real-time protection of large-scale GPU clusters and AI workloads through ASIC-powered performance and 400 GbE connectivity, optimising both security and cost efficiency across Fortinet’ s high-end data centre 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 defences that inspect and sanitise 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 centres
By combining these capabilities, the Secure AI Data Centre 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.
This launch extends Fortinet’ s legacy of leadership in performance, consolidation and AI-driven security. With the Secure AI Data Centre solution, Fortinet sets a new benchmark for protecting AI environments at scale, delivering the resilience, trust and operational simplicity enterprises need to confidently bring AI workloads into production.
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