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Secure AI at every layer and transform security from reactive to proactive
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FortiAI protects your entire AI ecosystem—infrastructure, models, workloads, data and supply chains—while leveraging unified AI intelligence across the Fortinet Security Fabric to defend against threats at machine speed. Our unified defense secures LLMs, prevent shadow AI and data leaks through real-time scanning and risk-based access, and block AI-driven attacks in less than one second with minimal false positives. The mature ML engine and GenAI capabilities enables inline inspection, automated threat hunting, rapid response, and secure GenAI adoption—delivering proactive protection for AI and with AI.
FortiGuard IPS uses advanced AI/ML for enhanced threat detection to enable deep-packet inspection, anomaly spotting, and coordinated response. It blocks known and suspicious threats pre-impact while minimizing false positives for proactive defense against evolving AI-driven malware.
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FortiAI-Protect lets you discover AI applications in use and understand their categories, use cases, risk levels, and comprehensive log details. It also blocks unauthorized prompts.
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Secure GenAI adoption is enabled with full visibility into usage and data sharing. You can apply guardrails, monitor activity, and adjust policies in real time. User coaching drives correct behavior and captures artifacts for intent investigation.
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FortiAI-Protect uses AI for real-time zero-day detection via static and dynamic analysis, spotting unknown malware with ML models. It has a low-latency processing option, enabling swift risk prioritization via dynamic scoring and exploitability intel for automated response.
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FortiAI-Assist boosts NOC operations from day 1 to day N with automated SD-WAN config generation, syntax validation, policy creation, VPN diagnostics, network performance troubleshooting, and one click to execute proposed fixes.
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FortiAI-Assist enables secure and sanctioned GenAI adoption with full visibility into usage and data sharing. Apply essential guardrails, monitor activity, and adjust policies in real time. The platform provides user coaching to drive correct behavior and captures vital artifacts for in-depth investigation and understanding of user intent.
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FortiAI-Assist delivers intelligent operations through dynamic baselining, trend analysis, and proactive troubleshooting. It performs automated triage, forecasting, and preventive actions while continuously fine-tuning configurations across the Fabric for optimal performance.
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FortiAIGate is a secure gateway for LLMs that provides intelligent routing, cost control, and GPU-accelerated performance. It safeguards AI operations by filtering and sanitizing all inputs and outputs to prevent data leakage, prompt-based attacks, and DDoS threats.
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This solution provides robust API protection specifically for LLMs. It filters and sanitizes all user inputs to prevent malicious prompts and attacks, while also securing outputs to stop sensitive data leakage. The system also defends against bot-driven abuse and DDoS attacks.
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This solution provides comprehensive oversight by monitoring application usage and supervising data flows to identify suspicious movements. It logs and tracks LLM interactions, creating a detailed audit trail so you can meet stringent compliance requirements for AI and data security.
Learn about FortiAI-ProtectFortiAI embeds sixth-gen ML and GenAI across the Fortinet Security Fabric. Leveraging FortiGuard Labs AI-driven threat intelligence, the solution:
Fortinet embeds diverse AI technologies in solutions across the Fortinet Security Fabric to deliver advanced AI-driven security and automation without additional complexity.
The AI/ML-powered FortiGuard IPS Service from Fortinet combines near-real-time intelligence with thousands of intrusion prevention rules to detect and block known and suspicious threats before they ever reach your devices.
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It directly addresses the security skills gap and alert fatigue by automating complex tasks like incident investigation and policy tuning. It also provides deep visibility into AI application usage, helps secure your own AI projects from data leaks and misuse, and dramatically speeds threat response times.
It provides full visibility into all GenAI usage across your network. You can apply guardrails to control which applications are sanctioned, monitor for sensitive data sharing, coach users on correct behavior, and capture forensic artifacts for auditing and investigation.
Yes. By using advanced deep learning models trained on Fortinet's global threat intelligence, FortiAI can analyze file behavior and network traffic to identify and block never-before-seen malware and zero-day exploits that bypass traditional signature-based defenses.
It acts as a force multiplier for your SOC analysts. It can instantly summarize incidents, recommend and implement remediation actions, automate complex playbooks, and explain threats in plain language, freeing your team to focus on strategic tasks.
It is designed to integrate seamlessly across the Fortinet Security Fabric. It enhances products like FortiGate, FortiSIEM, and FortiAnalyzer with AI-powered capabilities, maximizing the value of your existing security infrastructure.
FortiAI provides security for the AI life cycle. It helps you assess risks in AI models, monitor for model evasion attacks (like prompt injection or data poisoning), and enforce access controls to protect your proprietary models and training data.
FortiAI models are continuously trained and validated on one of the world's largest and most diverse threat intelligence datasets. Its recommendations are based on real-world telemetry and are designed to be explainable, providing the reasoning behind its actions to build analyst trust.
As a deeply integrated component of the Fortinet platform, deployment is streamlined. It receives continuous updates and new threat intelligence automatically through FortiGuard AI-Powered Security Services, requiring minimal ongoing maintenance from your team.
The ROI is measured in three key areas: Operational Efficiency (faster MTTR, reduced manual tasks), Risk Reduction (prevented breaches, secured AI adoption), and Cost Avoidance (doing more with existing staff and tools, avoiding fines from AI misuse).