The Problem With AI Visibility

#ai #geo #seo #aeo

Everyone's selling dashboards. Nobody's selling leverage.

I've spent the last several months deep in the AI visibility space — both as someone building in it and as a founder trying to understand why none of the existing solutions were actually helping move the needle. And I kept running into the same wall.

You pay for a platform. It tells you whether your brand shows up in ChatGPT. Maybe it gives you a score. Maybe it tracks your competitors. And then... it just sits there. A fancy mirror.

This feels exactly like early SEO all over again — everyone's monetizing the measurement, nobody's solving the problem underneath it.

The real issue: data without direction

The core failure of most AI visibility platforms right now is that they conflate tracking with strategy. Knowing that a competitor shows up in 80% of responses when someone asks "best project management tool for remote teams" — and you don't — is useful signal. But it's not a plan.

What actually matters isn't just that you're missing. It's understanding why you're missing, and what to fix.

Right now, most solutions hand you a report and leave you to figure out the rest. Some founders I know just test prompts manually. Others cobble together scripts to automate it. It's still very early, and the gap between measurement and action is real.

The 99% problem in this space: platforms give you data and reports, but none of them tell you how to fix and optimize. That's what the market actually needs.

What AI models are actually doing

Here's the framing shift that changed how I think about this:

AI agents aren't ranking your pages like Google does. They're trying to understand your company — what you do, who you serve, whether you're a fit — and then synthesizing an answer on behalf of a buyer who may never even visit your site. These agents behave like very impatient analysts. They skip marketing fluff entirely and jump straight to the structured, factual parts of a page they can quote.

So the question isn't "do I have good content?" It's: can an AI model parse, trust, and cite me at scale?

The structural gaps are almost always the same:

No llms.txt (basically robots.txt but for AI crawlers — tells them what you do and what pages matter)
Pricing pages buried in fluff instead of clean comparison tables
Support docs locked behind auth walls agents can't reach
No structured FAQ addressing the actual questions buyers ask

Companies with worse traditional SEO sometimes score better for AI readability simply because their site architecture is cleaner. A simple, well-structured static site beats a bloated enterprise site with 47 tracking scripts every time.

Multi-domain mentions are also massively underrated. A lot of people jump straight to content rewrites when the deeper issue is that AI models simply haven't seen the brand mentioned enough times across trusted sources to feel confident citing it. Review sites, GitHub, forums, third-party docs — that's where AI confidence gets built.

What I found actually works

After months of frustration with solutions that only showed visibility data but never helped you actually close the gaps, I started exploring what a proper solution would look like.

The core issue: most platforms stop at "you're invisible here." A real solution would need to identify the specific prompts where competitors appear and you don't, then generate concrete content recommendations to close that gap.

For example: you see your competitor shows up in ChatGPT for "best CRM for nonprofits" and you don't. The next step should be automatic: analyze your competitor's content and generate a specific plan: "You need an FAQ answering 'How does nonprofit pricing work', a comparison table of features, and schema markup for 'nonprofit organization' entity."

Then, instead of handing off the work to you, a real solution would:

Generate the actual code — Auto-create the FAQ/Product/Article schema markup so you don't have to guess formats
Map the gaps — Show you exactly which topics and entities are missing from your content
Audit the structure — Identify what's preventing AI agents from parsing your pages (missing headers, thin content, etc.)
Publish directly — Connect to your CMS so changes publish without switching apps
Prove the impact — Connect GA4 to show whether optimizations actually drove revenue

Most platforms give you insight. They don't give you the tools to actually execute. They don't tell you what to write. They don't generate the schema. They don't show you which gaps are worth closing.

That's the difference between "you're losing" and "write this specific thing and you'll win."

Building the solution

I decided to stop waiting for the right tool and build it. Citatra is built to do exactly this — turn visibility gaps into concrete action plans all while being open-source, and having a cloud version more affordable then competitors.

Instead of showing you a score, Citatra:

Identifies your specific gaps — Finds the exact prompts where competitors show up and you don't (the ones worth optimizing for)
Analyzes the root cause — Uses semantic analysis to show you what topics/entities/structure elements are missing from your content that competitors have
Generates optimization recommendations — Tells you exactly what content to create, what FAQ questions to answer, what schema to add
Builds the technical foundation — Auto-generates JSON-LD schema, provides HTML/structure audits, flags what needs to change
Removes the switching cost — Integrates with WordPress, Webflow, Shopify so you can publish changes without leaving the platform
Proves the ROI — Connects to GA4 so you can see which optimizations actually drove visits and conversions

This is the execution layer most tools completely skip. You don't get a score and a report. You get a specific plan: "Add this FAQ, add this comparison table, add this schema, publish it, and here's the revenue impact."

The difference matters. When your competitor shows up for a query and you don't, you now know exactly why and exactly what to fix. No guessing. No more staring at a dashboard wondering what to do next.

Some thoughts on this space

Lot of people I talk to in the AI visibility space are sleeping on how fundamental this shift is. If your site isn't structured for machines to parse it, you don't just rank lower — you essentially don't exist in the 2026 buying cycle.

The window to get ahead of this is right now. Most founders haven't even started thinking about this problem. The ones who do are going to have a massive competitive advantage.

If you're building in this space or have been frustrated by the limitations of existing solutions, I'd be curious to hear what you've discovered. What gaps have you found? What approaches have worked?

Feel free to message me or leave a comment — always interested in talking with other people thinking about this problem deeply.