What does AI say about your brand?

Each engine agent measures five dimensions of your AI visibility: Visibility (do you appear in AI answers — your AI citation rate, and whether you're the lead pick), Competitors (who appears instead of you, with AI share of voice), Brand Accuracy (is what the engine says about you true), Sources (which websites shape the answer) and Sentiment (how the engine talks about you). Every scan stores the complete AI responses, so every score links back to the evidence that produced it. Scans re-run automatically every two weeks to track movement.

Two things: per-engine depth and evidence. Most AI visibility trackers blend engines into one averaged score. Storyzee runs a dedicated agent per engine through the engine's own native API — the same responses real users see — and grades each engine separately. And every metric links back to the actual AI response that produced it, so you audit findings instead of trusting a black box.

Five engines today: ChatGPT (OpenAI), Perplexity, Gemini (Google), Claude (Anthropic) and Grok (xAI). Each is probed through its own official API with web search enabled, so responses match what real users get. New engines are added when they reach meaningful consumer adoption.

Every two weeks, automatically. Each scan is archived with its full AI responses, so your history builds into dated trend lines — visibility, share of voice, sentiment and accuracy over time. No manual re-runs needed.

No. Storyzee works entirely from the outside, the way a buyer would: it asks the AI engines questions and analyses the answers. There is no script to install, no analytics to connect, no site access to grant. During onboarding, Storyzee's researcher builds your brand profile from public information, which you review and correct before the first scan.

Yes. Scans are market-scoped: queries are generated in the language your buyers actually use, for the market you target. A brand can monitor several markets in parallel — for example France in French and the UK in English — each with its own scans and its own history.

Every scan ends with prioritized actions: correct the wrong facts the engines repeat, win the sources that cite competitors but not you, restructure the pages the engines can't extract. You can execute them with your team or agency — or Storyzee's services team can do it with you.

Each AI engine uses different training data, different retrieval augmentation methods and different ranking logic. ChatGPT relies heavily on web crawl data and has specific partnerships. Perplexity performs real-time web search and prioritizes recent, citable sources. Gemini draws from Google's search index and Knowledge Graph. Claude uses a distinct training corpus. Grok integrates X/Twitter data. A brand that scores well on Perplexity may score zero on ChatGPT — which is exactly why Storyzee runs one dedicated agent per engine and never blends the results.

Rarely. In most cases, improving AI visibility means optimizing what you already have: restructuring existing content in BLUF (Bottom Line Up Front) format so AI engines can extract clear answers, adding JSON-LD structured data (Organization, FAQPage, BreadcrumbList), creating an llms.txt file, opening robots.txt to AI crawlers (GPTBot, ClaudeBot, PerplexityBot), and fixing inconsistencies across third-party directory listings. A full site rebuild is only recommended when the architecture fundamentally prevents AI crawling or content extraction.

BLUF — Bottom Line Up Front — is a content structuring method where every section leads with the answer before providing context and evidence. AI engines extract answers by identifying the first complete, factual statement that directly addresses a query. Content structured in BLUF format gives AI engines a clean, citable extract immediately — instead of making them parse through introductions, storytelling or background.