Our 97% SEO Score Gets Us Ignored by AI. Here's Our Plan to Fix It.

As the founders of an AI Search Optimization platform, we believe in radical transparency. We build tools to give businesses a clear, data-driven view of how AI models perceive them. So, it’s only fair that we turn that lens on ourselves.

Recently, we did just that. We ran a comprehensive technical SEO audit on our own website, searchify.ai. The result? A score of 97.33%—a number that would make any SEO professional proud. Our site is fast, secure, mobile-friendly, and structured for crawlers. By all traditional measures, we’re doing everything right.

But then came the shock.

When we asked AI models like ChatGPT, Perplexity, and Google's AI Overview the questions our potential customers are asking—queries like “best AI visibility tools” or “how to improve brand mentions in AI answers”—Searchify was nowhere to be found. We were a ghost. Our technical excellence was met with digital silence.

This is the AI Visibility Paradox in action, a concept we've explored before but are now experiencing firsthand. It was a humbling and powerful wake-up call: for the new gatekeepers of search, our traditional SEO score was almost irrelevant.

The Diagnosis: Why AI Search Ignores Perfect SEO

Our initial confusion quickly turned into a diagnostic exercise. Why would a technically sound website be invisible to AI? The answer lies in a fundamental misunderstanding of how these new systems work. AI models are not just crawlers indexing keywords; they are synthesis engines building an understanding of the world based on trust and authority.

As explained by Search Engine Land, generative engines assess content based on signals of accuracy, authority, and transparency. A high technical SEO score signals a well-built house, but it doesn't prove that a trustworthy expert lives inside.

This is where frameworks like the AI Visibility Pyramid, detailed by Animalz, become so useful. The pyramid has three layers:

1. Base Layer: Traditional SEO. This is the technical foundation. We had this covered with our 97% score.
2. Middle Layer: Context & Content Strategy. This involves creating content that directly answers user questions. We have a solid library of guides and playbooks, so we're making progress here.
3. Top Layer: Trust & Authority Signals. This is about building credibility across the web, through third-party validation. This was our missing piece.

AI models are designed to reflect a consensus of trust. They learn who to recommend not just from a brand's own website, but from what the rest of the internet says about them. The data is stark: a staggering 85% of brand mentions in AI search come from third-party sources, not the brand’s own site [1]. This includes reviews, media mentions, and discussions on community platforms.

Our Authority Deficit: A Tale of Two Audits

To confirm our diagnosis, we conducted a DIY AI Visibility Audit on ourselves and compared the results to an established player in a related space. We didn't name them, but we analyzed their digital footprint to understand why AI models consistently recommended them.

The results were clear. When we prompted AI models with relevant commercial queries, the competitor appeared frequently. Their success wasn't accidental; it was built on a foundation of off-site authority signals that we, as a new startup, simply hadn't developed yet.

Here’s what they had that we didn't:

• A Deep Well of Social Proof: They had hundreds of positive, detailed reviews on G2 and Capterra. Each review is a verifiable, third-party signal of trust and experience.
• Consistent Media Mentions: They were frequently included in industry listicles,