Your site looks fine to Google. It might be invisible to AI.

Your site looks fine to Google. It might be invisible to AI.

Traditional SEO is no longer the whole game.

A growing share of discovery now happens inside tools like ChatGPT, Claude, Perplexity, Grok, and Google AI Overviews. But most websites are still built mainly for humans and traditional search engines. That creates a new problem: a site can look polished, rank decently, and still be much harder for AI systems to crawl, interpret, and cite than most teams realize.

That gap is exactly why we built [ConduitScore]

ConduitScore scans a public website and evaluates the technical and content signals that affect whether AI systems can access, understand, and surface it. Today, it checks 14 signals across 7 categories: crawler access, structured data, llms.txt, content structure, technical health, citation signals, and content quality. It then shows what is helping, what is hurting, and what to fix first. :contentReference[oaicite:1]{index=1}

AI visibility is not the same as SEO

Most SEO tools are built to answer questions like:

• Are we ranking?
• Are our pages indexed?
• Are we targeting the right keywords?

Those still matter.

But AI systems evaluate websites differently. They are also asking:

• Can I access this content cleanly?
• Can I tell what this company actually is?
• Is the page structure easy to parse?
• Are there enough trust and entity signals to cite this confidently?
• Is the content clear enough to extract into an answer?

That is a different layer of readiness.

And many sites are weaker there than they think.

Most sites are not broken. They are leaking AI visibility.

What we kept seeing was not one catastrophic issue.

It was a pattern of smaller problems that add up:

• blocked or unclear crawler access
• weak or missing schema
• no llms.txt
• poor content structure
• weak citation and trust signals
• thin page-level explanations
• missing canonical or indexing hygiene
• vague company/entity signals

Individually, each one can look minor.

Together, they make it much harder for AI systems to understand what your site is, what it offers, and whether it is safe to use as a source.

That is why a site can look fine to a human, look fine in a basic SEO crawl, and still underperform in AI-generated answers.

What ConduitScore actually checks

We wanted something more useful than vague advice like “make your site more AI-friendly.”

So ConduitScore measures concrete signals.

On the site today, those checks include things like GPTBot, ClaudeBot, PerplexityBot, and OAI-SearchBot access, sitemap fetchability, Organization and WebSite schema, llms.txt, canonical tags, noindex issues, HTTPS, contact/entity/trust signals, semantic HTML structure, title quality, and meta description quality. :contentReference[oaicite:2]{index=2}

The point is not just to generate a score.

The point is to answer a much more practical question:

What is blocking AI visibility right now, and what should we fix first?

That is why ConduitScore does not just spit out a number. It also shows the top issues holding the site back and prioritizes the highest-impact fixes first. The sample reports on the site follow the same pattern, including clear “what’s working,” “minor improvements,” and specific fix recommendations. :contentReference[oaicite:3]{index=3}

The shift teams need to make

The old mindset was:

How do we rank?

The new mindset is:

How do we make our site easy for AI systems to read, trust, and surface?

That does not replace SEO. It expands it.

Google rankings still matter. But if more product discovery, research, and comparison behavior is happening inside AI tools, then being easy for those systems to interpret becomes a real growth issue.

This is especially true for:

• SaaS companies
• agencies
• SEO teams
• ecommerce brands
• content-heavy sites that depend on being cited or summarized accurately

That is also why ConduitScore is positioned less like a traditional SEO audit and more like an AI visibility diagnostic. The homepage is explicit about that difference: SEO tools show how you rank in search engines, while ConduitScore is focused on whether AI systems can read, interpret, and surface your site in AI-generated answers. :contentReference[oaicite:4]{index=4}

The biggest wins are usually boring

The good news is that low AI visibility usually does not mean your site is fundamentally bad.

It usually means your site is missing a handful of machine-readability and trust signals that are fixable.

In practice, some of the highest-leverage fixes are often pretty boring:

• allowing the right crawlers
• improving schema
• adding a real llms.txt
• cleaning up headings and semantic HTML
• improving intro copy and summaries
• making entity and trust signals more explicit
• fixing canonical and indexing issues

These are not flashy changes.

But they reduce ambiguity.

And for AI systems, ambiguity is expensive.

Why we built ConduitScore

We built [ConduitScore] because this problem is becoming real before most teams have tooling for it.

More companies are asking versions of the same question:

Can AI actually see our site clearly — and if not, why not?

That is what ConduitScore is meant to answer.

Not with hype.
Not with hand-wavy AI SEO language.
With a concrete scan, a score, a breakdown of issues, and a prioritized fix list.

If you want to check your own site, run a scan at [conduitscore.com]