AI Information Architecture Audit
Deep-scan any website to see exactly how AI engines read, interpret, and rank its content
What is AI-IA?
AI Information Architecture (AI-IA) is the practice of structuring your website so that large language models — GPT, Claude, Gemini, Perplexity, and others — can reliably discover, understand, and cite your content. Traditional SEO optimises for Google's crawler. AI-IA optimises for AI reasoning engines that use entirely different signals: knowledge graphs, semantic context, provenance trust, and vector-friendly content atomicity.
Brands with strong AI-IA are cited as authoritative sources in AI-generated answers. Brands with weak AI-IA are invisible — even if they rank #1 on Google.
HOW THE AUDIT WORKS
Crawl & Fetch
We retrieve your robots.txt, llms.txt, sitemap, and homepage HTML to understand how your site presents itself to bots.
AI Analysis
Three parallel LLM calls evaluate your knowledge graph depth, semantic tagging quality, thematic structure, and internal linking.
Score 7 Dimensions
Each dimension is scored 0–100: Knowledge Graph, Semantic Tagging, Content Atomicity, AI Accessibility, Internal Linking, Provenance, and Multimodal IA.
Fix Roadmap
Priority-ordered fixes are generated with effort estimates and expected impact so your team knows exactly what to tackle first.
7 SCORED DIMENSIONS
Knowledge Graph
Schema markup, entity relationships, and structured data that AI engines use to understand who you are.
Semantic Tagging
How well your content is tagged with semantic HTML, ARIA labels, and machine-readable metadata.
Content Atomicity
Whether content is broken into discrete, referenceable chunks that AI can cite independently.
AI Accessibility
llms.txt presence, crawler permissions, server-side rendering, and API endpoint availability.
Internal Linking
Depth of navigation, thematic silos, and whether key pages are reachable within 2–3 clicks.
Provenance & Trust
Author signals, citations, Wikipedia presence, and third-party validation that AI trusts.
Multimodal IA
Alt-text quality, image metadata, video transcripts, and non-text content AI can parse.
Visual map of how your content hierarchy aligns with how AI engines categorise topics — from broad categories to specific product pages.
Your AI-IA score vs. industry peers and top performers, so you know if you're leading or lagging in your space.
Quick wins, medium-term improvements, and long-term structural changes — all prioritised by effort vs. impact.
WHO SHOULD RUN THIS AUDIT
Brand Marketers
Understand why competitors appear in AI answers and you don't — and get the exact fixes to close the gap.
SEO Professionals
Your traditional SEO toolkit doesn't measure AI readiness. This audit fills that gap with AI-native metrics.
Web Developers
Get a technical punch-list: schema gaps, missing llms.txt, crawler blocks, and SSR issues that hurt AI visibility.
CMOs & Strategists
Benchmark your brand's AI presence against the market and build a data-backed roadmap to own AI-generated narratives.
FREQUENTLY ASKED QUESTIONS
How is this different from a regular SEO audit?
Traditional SEO audits optimise for Google's PageRank algorithm — backlinks, keywords, and page speed. AI-IA measures completely different signals: how well your site's knowledge graph, semantic structure, and content atomicity enable LLMs to confidently cite you.
Does a high Google rank guarantee a good AI-IA score?
No. Many #1-ranked sites score below 40 on AI-IA because they were built for keyword density, not for AI comprehension. Some newer brands with modest SEO rankings have excellent AI-IA and appear frequently in AI answers.
What is llms.txt and why does it matter?
llms.txt is an emerging standard (similar to robots.txt) that tells AI models which pages they're allowed to use for training and answering. Without it, AI crawlers must guess — and often skip your most valuable content.
How often should I re-run the audit?
We recommend running it after significant site changes, monthly for active brands, or when you notice a drop in AI citation frequency. The competitive benchmark updates automatically each run.
What is content atomicity?
Content atomicity refers to how well your pages break information into discrete, independently-referenceable units. AI models can't easily cite a 5,000-word wall of text, but they can cite a clearly-labelled section, FAQ item, or data point.
Can I audit a competitor's website?
Yes. Enter any domain to audit it. This is especially useful for understanding why a competitor appears in AI answers for your category and what structural advantages they have.
Run an audit
Evaluates knowledge graph depth, semantic tagging quality, AI crawler access, content atomicity, internal linking, provenance signals, Theme Pyramid coverage, Golden Rule compliance, and multimodal readiness. Takes ~20 seconds.