Notra

Marketing and growth teams want to know whether their brand shows up when buyers ask ChatGPT, Claude, Gemini or Perplexity for recommendations, and if not, who gets mentioned instead. Today they have no visibility into mention rates, ranking position, or share of voice across AI engines, nor into which AI crawlers and agents are visiting their site and why. Without this, they cannot tell whether an AI bot visit is a training crawl, an indexing pass, or a real citation that drove a reader to their page. They also lack a way to identify which buyer questions AI engines already answer without mentioning the brand, so content gaps go unaddressed.

Notra is a GEO (Generative Engine Optimization) tool that asks ChatGPT, Claude, Gemini, Perplexity, Grok and other models the questions a company's buyers would ask, then reports mention rate, average position, and share of voice against named competitors, broken down by engine and language. It separately tracks AI traffic from 66 known agents, labeling each visit as model training, index building, an answer citation, or a human referral click, so a crawler fetch is never confused with a citation. The product surfaces content gaps, which are questions engines answer without citing the brand, ranked by how winnable they look, and its Write feature can draft a brief and a guide, listicle or comparison post for an approved gap. Integration for traffic tracking is done via an @usenotra/geo proxy or middleware for frameworks like Next.js, Nuxt, Astro and SvelteKit rather than a script tag, and teams can enable zero data retention so prompts and answers are not kept by model providers.