Step 1: Enter Your URL
Provide your website URL and a brief description of what your organization does and who it serves. The tool uses this context to evaluate whether your site's structural signals accurately represent your business.
The AI Visibility Audit Tool examines the structural foundation of your site and tells you exactly what AI systems can — and cannot — read, infer, and cite about your business.
This is not a keyword report or a prompt strategy. It is a technical and structural audit of the layer that exists before AI citation begins. Most sites fail here silently. The tool tells you specifically where and why.
Get Notified at LaunchLaunching April 1, 2026. Sign up to be the first to know when it goes live.
The AI Visibility Audit Tool examines four areas. These are the structural signals AI systems use to decide whether your content is readable, trustworthy, and citable.
The tool examines how your pages are built at the HTML level. This includes whether content exists in crawlable source or is injected by JavaScript, how your heading hierarchy is organized, whether your primary value proposition is readable before any script runs, and whether your interactive elements (forms, quizzes, results) have their content present in the DOM.
The tool examines what AI systems can infer about your organization from your site's machine-readable signals. This includes your schema markup type, whether your schema graph is linked, what entity information is present (name, address, service area, language), and whether those signals are consistent across pages.
Based on the findings, the tool identifies the specific structural changes most likely to improve AI citability. These are prioritized by impact — the changes that close the largest gaps first.
The tool identifies patterns that actively reduce citation confidence: static publication dates, JavaScript-dependent content, unlinked schema entities, missing organization data, and architecture choices that signal low crawlability to AI systems.
Not included: Keyword research, prompt strategy, content recommendations, or paid search analysis. The tool covers the structural foundation. Everything else sits on top of it.
Provide your website URL and a brief description of what your organization does and who it serves. The tool uses this context to evaluate whether your site's structural signals accurately represent your business.
The AI Visibility Audit Tool reviews your site against our structural framework — page source, schema markup, entity signals, JavaScript dependency, and content crawlability. The audit criteria are based on our published research from controlled experiments with real traffic.
Your audit report covers all four areas with specific findings for your site. Prioritized recommendations tell you exactly what to fix first. No call required — the report stands on its own.
The AI Visibility Audit Tool launches April 1, 2026. Sign up below to be notified the moment it goes live.
The audit framework is based on controlled experiments measuring actual AI crawler behavior, citation frequency, and referral traffic across live sites.
Published findings include:
Why AI citation matters: live data showing ChatGPT outconverting Google on a domain with zero backlinks within 60 days. The case for why structural AI visibility is worth getting right.
Read the paper →Field notes from a controlled experiment documenting AI crawler behavior, citation patterns, and structural decisions on a live site, with specific findings on schema type, JavaScript dependency, and crawlability.
Read the field notes →The AI Visibility Audit Tool examines the structural foundation of your website across four areas: page structure (how your HTML is built and what is readable before JavaScript executes), context structure (what AI systems can infer about your organization from machine-readable signals like schema markup), areas of opportunity (specific changes most likely to improve how AI systems read and cite your content), and areas of weakness or exposure (patterns that actively reduce citation confidence, such as JavaScript-dependent content or unlinked schema entities). The tool does not include keyword research, prompt strategy, or content analysis — it examines the layer that exists before those decisions matter.
An AI Visibility Audit examines signals that are largely invisible to traditional SEO tools. Where an SEO audit focuses on rankings, backlinks, and keyword optimization, an AI Visibility Audit examines whether AI systems can correctly read, interpret, and cite your content. The key differences are in schema graph integrity, JavaScript dependency, content crawlability, and entity signal consistency — technical factors that determine whether an AI answer engine will surface your organization when a user asks a relevant question. A site can rank well in Google and still be effectively invisible to AI citation systems.
Yes. The AI Visibility Audit Tool is free and will remain free. We are building toward an AI-native web where agentic systems can correctly understand and recommend businesses. For that to function, the structural foundation across sites needs to reach a minimum level of coherence. We benefit from that ecosystem maturing. The tool itself is an investment in the infrastructure we are trying to help build.
The AI Visibility Audit Tool launches April 1, 2026. Sign up on this page to be notified the moment it goes live.
The tool asks for your website URL and a description of what your business does and who it serves. This context helps the tool evaluate whether your site's structural signals accurately represent your organization. No technical knowledge is required.
Results are available immediately after the tool completes its analysis. The full report covers all four audit areas with specific findings and prioritized recommendations for your site.
No. The report is delivered directly — no call required. Contact information is included if you want to discuss implementation, but the audit is complete and actionable on its own.
The report includes specific findings for your site and prioritized recommendations. Most findings — schema updates, content structure changes, removing JavaScript dependencies from crawlable content — can be executed by any developer familiar with the site's codebase. For complex cases, Minnesota AI publishes guidance and frameworks to help teams work through the changes independently.
The audit framework is based on controlled experiments published on the Minnesota AI research page and daveedvalencia.com/research. Key published findings include a controlled experiment measuring a 24.9% conversion rate from ChatGPT on a new domain within 60 days, and field notes from a controlled experiment documenting AI crawler behavior, citation patterns, and which structural decisions affected visibility on a live site. Every structural criterion in the audit is traceable to a documented experiment with real traffic and measurable outcomes.
The tool requires a publicly accessible URL to perform its analysis. Staging environments behind authentication are not supported. If you are pre-launch and want to discuss a structural review, contact us directly at [email protected].