Lumidian queries each AI model directly and measures how often your brand appears in their responses. No scraping, no proxies — the same APIs that power ChatGPT, Claude, Perplexity, and Gemini.
Transparency matters. If you're going to act on a visibility score, you should know exactly how it's calculated, what it represents, and what can move it. This page explains every part of the process.
Every model we query answers against the live web. Each one reaches for sources differently, so we treat them as four independent readings of what the web says about you today.
OpenAI
OpenAI's native web search retrieves live results before answering, matching what users see in ChatGPT today.
Anthropic
Claude Haiku 4.5 with Anthropic's web-search tool. Issues up to three targeted searches per query before responding.
Perplexity
Search-grounded by design. Every answer is built from sources pulled at request time, with inline citations.
Google Search grounding is on for every query, so answers reflect current web context rather than static knowledge.
One number that tells you how visible your brand is across AI. Here's exactly what goes into it.
Prompts sent to each model
Your tracked prompts are sent to each AI model's API — ChatGPT, Claude, Perplexity, and Gemini. Each prompt is run multiple times per model to account for response variation.
Responses checked for mentions
Every response is analyzed for your brand name using both an exact case-insensitive match and a fuzzy normalized check that strips non-alphanumeric characters. A mention is detected if either method finds your brand.
Score calculated
Your visibility score is the percentage of queries where your brand was mentioned.
Per-model score is calculated this way for each AI model individually. Your overall visibility score is the average of every model your plan queries, so tiers with fewer models aren't penalized against tiers with more.
Errors excluded
If a query fails due to an API error or timeout, it's excluded from the denominator entirely. Your score only reflects responses that were actually received and analyzed.
3 runs per prompt per model. Each prompt is sent to every supported model three times to smooth out response variation. Which models run depends on your plan:
| Tier | Models queried |
|---|---|
| Free | Perplexity, Gemini |
| Starter | ChatGPT, Perplexity, Gemini |
| Growth | ChatGPT, Perplexity Pro, Gemini |
| Pro | ChatGPT, Claude, Perplexity Pro, Gemini |
We query each AI model's API directly — the same models that power ChatGPT, Claude, Gemini, and Perplexity.
Consistent, reproducible results
Direct API queries eliminate variation from account state, location, cookies, and session history. Every run uses the same conditions, so your scores are comparable over time.
Every answer comes from today's web
Every model we query runs against the live web — ChatGPT's native search, Claude's web-search tool, Perplexity's search grounding, and Gemini's Google Search integration. Scores reflect the web as it exists today, not a frozen snapshot from a model's training run.
Stable over time
Some tools scrape consumer chat interfaces, but those results vary by session and break when UIs change. Direct API queries give you stable, comparable scores that you can trend with confidence.
Every model we query is doing the same thing under the hood — searching the web for sources that answer the prompt, then composing an answer from what it finds. Four things consistently show up in the sources that get cited.
Fresh web content that answers the prompt
Reddit threads, Quora answers, and recent articles that mention your brand in the context of what the prompt is actually asking. Relevance to the question beats generic brand mentions every time.
Authority on sources AI search weights heavily
Wikipedia, major publications, and industry-specific subreddits that reliably surface in grounded searches. A mention on a domain the models already trust moves the needle.
Repeat mentions across independent sources
One mention on one site is easy to pass over. Three independent sources corroborating the same claim is much harder to ignore — that's when models start treating it as the default answer.
Prompt-term adjacency
Your brand name appearing near the prompt's core keywords on the source page. Proximity is how search-grounded models decide which mentions are relevant to the question being asked.