Platform

AI Visibility

Track where your brand appears in AI answers across engines, prompts, competitors, and buyer questions.

See it inside Findable

A live look at the Visibility module — score, engine breakdown, mentions and citations side by side.

findable.app / visibility
Live
Visibility score
61+8 vs last run
Mentions
128
Citations
47
Visibility by engine
Last 30 days
ChatGPT78%
Perplexity64%
Gemini51%
Google AIO42%

What it is

AI Visibility measures how often your brand is mentioned, cited, or recommended by large language models when people ask questions about your category. Instead of ranking on a page of blue links, your brand now needs to surface inside the answer itself — across ChatGPT, Claude, Gemini, and Perplexity. Visibility quantifies that presence.

Why it matters for AI search

Buyers increasingly start their research inside AI assistants. If the model doesn't mention you when someone asks for the best provider, you're invisible at the moment of decision. Visibility tells you whether AI engines know who you are, what you do, and when to recommend you — and how that compares to the brands answering those questions today.

The shift

"AI does not rank pages. It recommends brands."

How Findable helps

Findable runs your brand and category through real prompts on multiple AI engines, captures every answer, and detects mentions, citations, and recommendations. We aggregate the results into a visibility score, track it over time, and break it down by engine, prompt, funnel stage, and competitor — so you can see exactly where you appear, where you don't, and what's moving.

From AI answers to decisions

Visibility is a loop, not a one-time check.

  1. 1
    Run prompts
    Real category prompts executed across every covered engine.
  2. 2
    Capture answers
    Every answer, mention and citation is stored verbatim.
  3. 3
    Measure visibility
    Mentions, citations and recommendations roll up into one score.
  4. 4
    Track movement
    See what moved, where, and why — across engines and prompts.

Key capabilities

Visibility score
A single normalized score across engines and prompts.
Citation score
How often AI quotes sources that point to you.
Recommendation score
How often AI actively recommends you, not just mentions you.
Engine comparison
Side-by-side visibility for every covered model.
Trend analysis
Track movement across runs, not just snapshots.
Prompt performance
See which prompts surface you and which don’t.

Visibility changes by engine

Each AI engine sees the world differently. Findable surfaces per-engine deltas so you can see when one model starts recommending you while another stops — and act on it before it becomes a trend.

visibility / by-engine
EngineYouPeer avgΔ
ChatGPT78%71%+7
Perplexity64%69%−5
Gemini51%62%−11
Google AIO42%38%+4
visibility / trend
12-week trend
+23 pts
Improving

Visibility changes over time

A single score is a snapshot. Findable plots visibility across runs so you can connect movement to launches, content, and authority work — and prove what actually moved the needle.

What this allows teams to do

Without Findable
  • Guess which engines mention you
  • Assume your category prompts surface you
  • React to anecdotes
  • Talk about AI search
With Findable
  • Measure mentions per engine
  • Run real category prompts every week
  • Track visibility deltas across runs
  • Show AI search results to the board

What teams find

Anonymous examples from real Findable workspaces.

"
One SaaS brand discovered that two engines recommended it for half the buying-stage prompts — but a third never mentioned it at all.
Anonymous brand
"
One D2C brand grew visibility from 38 to 61 in six weeks by closing the source gaps surfaced by Findable.
Anonymous brand
"
One B2B team identified 47 high-intent prompts where competitors were recommended instead of them.
Anonymous brand

What you can see inside Findable

  • Visibility score across engines
  • Mentions and citation counts
  • Per-prompt coverage and rankings
  • Visibility by AI engine
  • Competitor visibility comparison
  • Visibility trends over time
  • Reasons visibility differs across models

Methodology

The AI Visibility Score combines three weighted components measured across a representative prompt set for your category: Presence (60%) — whether your brand appears at all, Coverage (25%) — the share of prompts where you show up, and Sentiment (15%) — how positively you're framed. Findable re-runs the prompt set on a configured cadence so trends reflect real shifts in AI behavior, not single-run noise.

Findable analyzes visibility patterns across multiple AI systems, prompt categories, industries, competitors, and citation sources to identify how brands are discovered, recommended, and referenced in AI-generated answers.

Examples of AI visibility analysis

Illustrative scenarios that show how AI assistants surface different sources for the same question across industries. These are examples, not actual customer data.

Healthcare
  • ChatGPT may recommend Mayo Clinic.
  • Gemini may cite NIH.
  • Claude may rely on peer-reviewed sources.
  • Perplexity may aggregate publisher references.
Consumer brands
  • ChatGPT may cite review publishers.
  • Gemini may use retailer and publisher sources.
  • Perplexity may surface editorial recommendations.
Executive education
  • AI engines may recommend schools based on citations, mentions, and authority signals.

How AI engines evaluate visibility

Modern AI assistants do not rank pages the way classic search engines do. They evaluate brands and entities using a combination of signals drawn from their training data, retrieval index, and live web sources:

  • Mention frequency
    How often a brand appears in AI-generated answers when users ask questions related to its category. A higher mention frequency means the brand is part of the conversation.
  • Citation frequency
    How often AI systems explicitly reference sources — such as websites, articles, or databases — that are associated with a brand. Citations signal that the AI considers the brand's content worth referencing.
  • Recommendation share
    How frequently a brand is explicitly recommended compared to competitors when buyers ask for the best option in a category. It reflects whether the AI presents the brand as a top choice.
  • Source authority
    How authoritative the sources discussing a brand are. When high-authority domains mention or cite a brand, AI systems are more likely to treat that brand as trustworthy and relevant.
  • Entity confidence
    How strongly AI systems associate a brand with a specific category, product, or topic. High entity confidence means the AI understands what the brand does and does not confuse it with generic terms or unrelated entities.
  • Competitive overlap
    How frequently brands appear together in AI recommendations. It reveals which alternatives the AI considers comparable and which decision spaces the brand is competing in.

Findable measures each of these signals across supported AI engines so teams can see what is driving — or limiting — their visibility.

Underlying research

Measured across millions of AI answer signals.

36,798
AI answers analyzed
75,295
Brand sentiment observations
10.38
Citations per AI answer

Primary AI research

Findable generates prompts and analyzes AI responses directly to measure how brands are mentioned, cited, and recommended across AI systems. This allows visibility to be measured from original AI answers rather than relying exclusively on aggregated datasets.

Learn more

Deeper guides on the concepts behind AI visibility.

Compare AI visibility platforms

Side-by-side comparisons with other AI visibility and SEO tools.

Related industry research

External references on AI search and generative answer engines.

External links open in a new tab.

Frequently asked questions

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