This French startup wants to tell brands what ChatGPT really says about them, and whether it drives clicks

For 20 years, brand visibility online meant one thing: where you ranked on Google.

Now executives are asking a different, more unsettling question: when someone asks ChatGPT, Perplexity, Google’s Gemini, or Anthropic’s Claude about our company, do we show up at all, and if we do, what do these AI “answer engines” actually say?

A French startup called Cockpyt AI says most marketing dashboards still can’t answer that. The company, now in MVP stage, is betting that the next big battleground isn’t the search results page, it’s the sentences AI models generate.

From SEO to “GEO”: the new fight is inside AI answers

The shift has a name: Generative Engine Optimization, or GEO. Think of it as SEO’s younger, weirder cousin, less about winning a blue link on a results page and more about getting mentioned (correctly) inside an AI-generated response.

That matters because Google dominance doesn’t guarantee AI visibility. A brand can rank No. 1 on a traditional search query and still never get cited when a user asks the same question in ChatGPT. The reverse can also happen: AI tools may recommend a brand that isn’t a top organic result.

The business stakes are rising fast. A recent case study in the French e-commerce world found a Shopify brand tripled sales attributed to AI-driven traffic after targeted work on its English-language site, suggesting these referrals can convert better than classic organic search. For marketers watching “zero-click” behavior grow, that’s a flashing warning light.

Why measuring AI visibility is so hard

Tracking Google rankings is relatively straightforward. Tracking AI mentions is not.

Large language models are non-deterministic: ask the same question twice and you can get different answers. They may also pull information dynamically from the web, run hidden follow-up searches in the background, or cite sources that don’t exist. That makes “brand visibility” in AI responses a moving target, and a nightmare to measure with old-school SEO logic.

Cockpyt AI was built specifically to tackle that measurement problem, rather than bolting an “AI tab” onto a traditional SEO platform.

Cockpyt AI’s pitch: a GEO-first dashboard built for marketers

Cockpyt AI is a SaaS product built by two French co-founders: one focused on SEO/GEO strategy and product, the other on engineering. Their core argument is simple: AI visibility requires a native tool designed around AI’s quirks.

“Measuring visibility in LLMs isn’t measuring a position on a search results page,” one co-founder said. “You have to test each prompt multiple times, across multiple models, with multiple variants, and then cross-check the results. It’s a different logic.”

The company is targeting three groups: in-house marketing leaders, SEO agencies expanding into GEO, and specialized freelancers who need a dedicated tool for client work. Cockpyt AI isn’t trying to replace full SEO suites, it wants to own a narrower category: AI-answer visibility.

Four features designed to show whether AI mentions actually matter

Cockpyt AI organizes its product around four core pillars, each aimed at turning messy AI outputs into something a marketing team can act on.

A single “Cockpyt Score” instead of a pile of vanity metrics

Rather than flooding users with dozens of charts, the platform rolls visibility into one composite metric: the Cockpyt Score.

It factors in whether the brand appears in an AI response, where it shows up among cited brands, and whether the response includes a link or contact path to the official site. The product also includes a “blocking rule” meant to prevent a common dashboard sin: flattering scores when the brand is effectively invisible.

Deep Scan: repeated tests across multiple AI models

The technical core is a feature called Deep Scan. Instead of sending one prompt to one model and treating the output as truth, Cockpyt AI runs multiple tests per prompt and varies internal parameters to map how responses change.

The goal is statistical stability, results that hold up despite the randomness baked into AI systems.

The tool also surfaces the hidden “fan-out queries” some models generate behind the scenes to build an answer. For marketers, that’s a rare window into what the model is actually trying to figure out before it responds, and which sub-questions might be shaping whether a brand gets mentioned.

Competitive intel: who’s taking your spot in AI answers

Knowing you’re missing is useful. Knowing who’s replacing you is actionable.

Cockpyt AI bakes in competitive analysis, including a global “share of voice” view across tracked prompts and a “threat radar” that flags competitors most likely to dominate responses.

For each prompt, users can drill down into brand and competitor positions, how frequently competitors appear, and, most importantly, the sources the AI model actually consulted. That source list can point teams to the specific sites and pages they may need to influence to break into the model’s citation set.

The big differentiator: tying AI visibility to real traffic in Google Analytics

Most GEO tools stop at “Are we mentioned?” Cockpyt AI wants to go further: “Did it drive visits?”

The platform connects directly to Google Analytics 4 and identifies traffic coming from major chatbots, including ChatGPT, Perplexity, Gemini, and xAI’s Grok. It pulls data daily and cross-references it with visibility scores.

In practice, that means a marketing team can see not just whether AI tools cite the brand, but how many site visits those mentions generate, bringing GEO closer to the familiar SEO workflow of pairing rankings with analytics and conversion data.

A product philosophy built for everyday use, and built in public

Cockpyt AI is also making a usability bet. The single score, the blocking rule, and a stripped-down dashboard are designed to be checked regularly, not once a month by a specialist.

The product includes a 15-step GEO checklist with prioritized actions and a progress bar, less “data theater,” more execution.

The company is also building in public: its roadmap is visible inside the app, and users can vote on what gets built next. In a space where product roadmaps are often closely guarded, that transparency is part of the brand.

What’s next on the roadmap

The team says it’s already working on more advanced metrics, including tracking how concentrated AI-cited sources are (and how that changes across model updates), identifying domains that repeatedly show up as sources, and monitoring visibility by specific model version.

Another planned feature aims to separate two kinds of AI visibility: “parametric” visibility (what the model learned during training) versus “dynamic” visibility (what it pulls from live web search). For marketers trying to influence outcomes, that distinction could determine whether they should focus on PR, content, technical SEO, or something else entirely.

The bottom line for marketers

Cockpyt AI is arriving as brands confront an uncomfortable reality: AI-powered answers can siphon attention without sending clicks, and traditional SEO tools don’t fully explain what’s happening.

If Cockpyt AI can reliably measure brand presence across multiple models, and connect that visibility to actual traffic, it could become a kind of barometer for the GEO era. For companies watching organic search soften without obvious changes to their SEO strategy, the next place to look may be the answers people are getting before they ever reach Google.