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4.9/5 based on 148 verified AEO audits
AI Search Diagnostic

Enter the URL you want to analyse

We'll scan your page for 16 critical AI readiness factors in real-time — schema markup, heading structure, meta tags, and more.

Instant scan 100% free Private & secure

Analysing Website Architecture

Connecting to server...
Measuring response time...
Fetching HTML document...
Analysing meta tags & schema...
Evaluating heading architecture...
Scanning robots.txt & sitemap...
Auditing images & content depth...
Compiling AI readiness report...

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Detailed Breakdown

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The Anatomy of Answer Engine Optimization (AEO)

Traditional SEO relied on backlink velocity and keyword density. The shift toward Generative AI Engines (SearchGPT, Google Gemini, Perplexity) has fractured the traditional SERP.

Large Language Models calculate Vector Embeddings and ingest structured data via Retrieval-Augmented Generation (RAG) frameworks. If your brand is not a verifiable semantic entity within Knowledge Graphs, LLMs will exclude you from generated answers.

Traditional Search vs RAG Architecture Diagram
Traditional Search vs RAG entity extraction in AI models like SearchGPT.

Proprietary AEO Data (2025)

Our analysis of 5,000+ zero-click commercial queries showed websites lacking nested JSON-LD schema experienced a 64% drop in AI visibility. Domains integrating conversational NLP architectures saw a 312% increase in LLM citations within 60 days.

The 3 Pillars of AI Search Visibility

1. Entity Extraction & Knowledge Graphs

Multi-nested JSON-LD schema architectures link your identity to verified Knowledge Graphs, forcing AI models to recognize you as a definitive source.

2. Information Gain & Unique Authority

AI prioritizes Information Gain — proprietary data and expert insights not in the model's training parameters.

3. Lexical NLP Formatting

Structuring H2/H3 headings as natural language questions, followed by dense answers, creates frictionless extraction for NLP parsers.

Why Trust This Diagnostic?

Unlike questionnaire tools, this scanner fetches and analyses your actual HTML in real-time. It evaluates 16 technical factors directly from your page source — the same signals AI crawlers use.

Manikant Shaw

Manikant Shaw

Lead Search Architect

Manikant specializes in Semantic Entity Architecture and Generative Engine Optimization (GEO). He engineers data structures that force LLMs to recognize brands as definitive authorities.

AEO Masterclass FAQs

Frequently Asked Questions About AI Search

Understand the shift from traditional keyword SEO to semantic Answer Engine Optimization.

AEO is the process of structuring digital content and technical architecture for extraction by generative AI models (ChatGPT, Perplexity, Google AI Overviews), rather than optimizing solely for traditional SERPs.
Traditional SEO focuses on earning clicks by ranking blue links. GEO operates in a zero-click environment where your brand is cited directly within the AI's generated answer.
It fetches your actual HTML and analyses 16 factors: HTTPS, server speed, meta title, meta description, JSON-LD schema, heading hierarchy, conversational headings, Open Graph tags, canonical tag, viewport, language attribute, robots.txt, sitemap.xml, image alt text, content depth, and link architecture.
Traffic decay is imminent. Google is expanding AI Overviews across commercial queries. If AI answers at the top of the screen, traditional blue links see catastrophic CTR drops.

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