About GenRankEngine

The Cost of Invisibility

While you rank #1 on Google, your competitor is frequently being cited as the sole recommendation in ChatGPT for high-intent prompts.

This is a silent pipeline leak.

Traffic didn’t drop. Pipeline did. Because the evaluation is happening inside the model, where traditional analytics cannot see it.

What GenRankEngine Is (and Isn’t)

GenRankEngine is an early-stage B2B SaaS that measures and tracks AI answer visibility at inference time across modern answer engines (ChatGPT, Gemini, Claude, Perplexity).

The product does not access training data, model weights, or proprietary retrieval systems.

All insights are derived from observable, repeatable outputs generated by AI models in response to high-intent prompts.

We do not sell "guaranteed rankings." We provide directional, probabilistic signals so you can defend your market validation.

Methodology: Signal → Risk → Action

We treat AI visibility as an engineering problem.

• 01
  Signal: Multi-Model Observation We run identical buyer-intent prompts ("Best alternative to X", "X vs Y pricing") across multiple models. We measure consistent inclusion patterns and model-specific gaps.
• 02
  Risk: The Displacement Scenario We identify where competitors are becoming the "default" answer. When AI answers collapse vendor comparison into one paragraph, exclusion means you are not in the consideration set.
• 03
  Action: Contextual Repair We track the citation sources and entity contexts that drive visibility. You use this data to adjust metadata and citations, then we re-measure to observe changes.

Who GenRankEngine Is For

This platform is designed for definitive Series B+ B2B SaaS companies in competitive categories.

It is for VPs of Growth and Heads of SEO who are already investing in organic search but are afraid of being displaced quietly by AI answers.

It is not for early-stage startups, e-commerce, or anyone looking for a "magic button" to force rankings.

Built by Engineers, Dogfooded Daily

We track this on our own product. We know the signal fluctuates. We know it is not deterministic. In fact, we use our own Perplexity Rank Tracker daily to monitor our own citation frequency.

We built GenRankEngine because we witnessed our own previous products losing visibility to competitors who were "hallucinated" as better alternatives simply because they had better citation density.