fortinet.com — AI Search Visibility Report
Overall score: 82/100
AI search visibility analysis for fortinet.com. LLMao scored fortinet.com 82/100 across 8 LLM-readiness categories including crawlability, semantic content, structured data, authority signals, and answer-engine clarity.
Analyzed URL
Category breakdown
- readability: 75/100 — Professional and clear, though high use of industry jargon (SASE, SD-WAN, CNAPP) without immediate definitions.
- schema_markup: 88/100 — Excellent Organization and WebSite JSON-LD, including Wikidata links, but lacks specific Product or Article schema on the home page.
- authority_trust: 85/100 — Strong social proof with Gartner Magic Quadrant mentions and clear contact info, but lacks individual author bios.
- citation_sources: 70/100 — Good use of internal reports and analyst data, but could benefit from more diverse external primary source citations.
- content_freshness: 95/100 — Excellent use of 2025 and 2026 dates in reports and metadata, showing high recency.
- content_structure: 80/100 — Clear navigation and logical grouping, though the homepage is heavy on navigation links versus long-form structured text.
- entity_definition: 75/100 — Strong brand consistency and clear 'About' information, but missing granular author entities.
- technical_accessibility: 85/100 — Good metadata and social tags; content is largely accessible, though heavily reliant on JS for menu interactions.
Top recommendations
- Add Visible Update Timestamps (Content Freshness): Implement explicit 'Last Updated' dates on product and solution pages to signal content recency to LLM crawlers.
- Expand Content-Specific Schema (Schema Markup): Implement FAQPage schema for product pages and Article/BlogPosting schema for the 'Latest from Fortinet' news items.
- Implement Author Person Schema (Entity Definition): Create dedicated author pages for researchers and executives mentioned in reports, linked via Person schema.
- Enhance External Citations (Citation & Source Quality): Include more outbound links to third-party validation sources (like NIST, MITRE, or IEEE) within technical descriptions.
- Update AI Crawler Directives (Technical Accessibility): Explicitly allow PerplexityBot and ClaudeBot in robots.txt to ensure optimal indexing by newer LLM search engines.