Platform Tools
Standard tools check for broken links and keyword density. An AI Website Audit checks if language models can actually read your text. If your technical setup blocks bots or lacks the right file structures, you simply disappear from conversational AI Answers. You need dedicated diagnostics to spot the exact errors that a normal Website Audit completely ignores.
Platform Tools
MetaFyAI breaks down every technical barrier. Chatbots and answer engines look for clean code, specific text files, and highly structured facts. If your technical foundation is confusing, AI Search engines will simply skip your content and quote a competitor. Our platform breaks down every technical barrier.
Check your robots.txt and server settings to ensure complete access for all major AI Crawlers. Confirm that bots are not accidentally blocked from your most critical pages.
Ensure your site provides a clean llms.txt file. An LLMs.txt Audit verifies this crucial markdown file acts as a direct map, guiding language models efficiently through your business content.
Run a precise Content Discoverability check. Measure if your core product pages and service descriptions can be easily extracted by generative search systems.
Execute a Structured Data Audit to verify that your schema markup translates perfectly to Answer Engine Optimization. Feed clear, structured facts directly to the bots.
Platform Tools
A generic site-wide score will not fix your traffic drops. Our diagnostic tools pinpoint the exact URLs that fail to support your overall AI Website Readiness.
Move beyond top-level warnings. See where formatting problems occur, identify which product pages are affected, and deploy targeted technical fixes for the pages that generate your revenue.
Isolate exact pages blocking generative bots.
Stop relying on blind, site-wide code changes.
Protect your most valuable product and pricing URLs.
Platform Tools
Stop drowning in massive lists of technical warnings. We turn complex data into clear, actionable recommendations that your development team can use instantly.
Understand what was detected, where it appears, and how urgently it must be addressed. Know exactly what to fix first to improve your AI Search visibility and secure your traffic.
Rank issues by their direct impact on search visibility.
Receive clear, step-by-step resolution paths.
Move from analysis to action without developer guesswork.
Platform Tools
Our platform streamlines the exact diagnostic process required to secure your position in conversational search.
Thoroughly crawl your domain to simulate how an LLM interacts with your pages.
Find the technical blockers currently hurting your overall Content Discoverability.
Rank issues by their direct impact on your AI Website Readiness so your team knows what to tackle first.
Apply clear, targeted code and text fixes to restore your visibility and dominate conversational engines.
Take Action
Ensure ChatGPT, Claude, and Gemini can actually read your content. Run a complete AI Website Audit to find and fix your hidden technical blockers.
What is the difference between a traditional Website Audit and an AI Website Audit?
A traditional Website Audit focuses on Googlebot indexing and securing blue-link rankings. An AI Website Audit specifically tests if Large Language Models can extract, parse, and accurately cite your direct answers in a conversational chat interface.
Why do I need an LLMs.txt Audit?
The llms.txt file acts as a clean markdown map specifically designed for generative AI bots. If this file is missing or broken, complex language models may misunderstand your site context. An LLMs.txt Audit verifies this exact setup to keep your site legible to machines.
How does AI Crawler accessibility impact my sales?
If generative engines cannot read your pricing, features, or product details because you blocked AI Crawlers, they simply will not recommend you. They will bypass your site entirely and recommend a competitor whose website is easier to parse.
What does a Structured Data Audit actually check?
A Structured Data Audit verifies that your schema markup (like FAQs, product specs, and business details) is formatted correctly for answer engines. These AI platforms rely heavily on clean structured data to deliver confident, factual responses to their users.
How often should we run an AI Readiness Audit?
Because major language models update their crawler behaviors and requirements frequently, running an AI Readiness Audit monthly ensures you catch new technical blockers before they cause a drop in your referral traffic.
