AI visibility platform
The evidence-first AI visibility platform
An AI visibility platform measures whether AI assistants mention, cite or recommend your brand when people ask real questions — and helps you improve it. Answerly checks your prompts across ChatGPT, Gemini, Perplexity and Google AI Overviews (Google AI Mode is in progress). It reports mention rate, citation rate and share of voice, separates a name-drop from a linked citation, finds the exact prompts where a competitor wins, and turns those gaps into a SERP-grounded content plan. Every number is shown with its sample size and margin of error, and the raw AI answer behind it is stored so you can verify it — a single AI reply is a sample, not a verdict.
One platform, three jobs
Measure visibility (mentions, citations, recommendations, share of voice), diagnose gaps (which prompts, which competitors, which sources), and act on them with a prioritized, SERP-grounded content plan. Most tools stop at the first job; the gap between a dashboard and a decision is where AI visibility work actually gets done.
The answer surfaces we measure
ChatGPT, Gemini, Perplexity and Google AI Overviews, with Google AI Mode in progress. Each is measured separately, because they retrieve and cite differently — a brand can dominate Perplexity and be invisible in AI Overviews. Blending them into one "AI rank" would hide exactly the difference you need to act on. We list a surface only once we can actually measure it.
Mentions vs citations vs recommendations
A mention is your brand named in the answer text. A citation is your website linked as a source. A recommendation is the assistant actively suggesting you. They move independently: you can be cited as a source while a competitor gets recommended in the prose. Answerly tracks the three as separate metrics rather than collapsing them into one vanity score.
Repeated sampling, stated uncertainty
AI answers are non-deterministic — the same prompt can name different brands on different runs. So each prompt is sampled repeatedly and every rate is reported with n and a 95% margin of error. A movement smaller than the error bar is labeled noise, never growth, and comparisons are weighted by sample size so a 2-run spot check never overwrites a 60-run baseline.
Evidence you can hand to a client
Every mention and citation links to the captured raw answer, with the engine and the date. When a client asks "how do you know?", the answer is a prooflink to the exact dialogue rather than a screenshot or a promise. Unverifiable entities — names the model returns with no real site behind them — are flagged instead of quietly inflating anyone's share of voice.
Competitor gaps at the prompt level
Share of voice tells you that you are behind. The prompt-level gap list tells you where: the specific questions where a rival is named or cited and you are absent, split into mention gaps and citation gaps because the two need different fixes — better on-page answers versus earning a presence on the third-party sources the model already trusts.
Prompt discovery from real demand
Tracking invented questions produces confident numbers about nothing. Answerly builds the prompt set from Google Search Console queries and Serpstat clusters, covering recommendation, comparison and problem intents, then prunes near-duplicates so runs go to coverage instead of ten phrasings of the same thing.
From gap to grounded action plan
Each gap becomes a brief grounded in the live top-10 SERP for that query — the answer, structure and entity claims come from what already gets cited, not from a template. Briefs carry status (planned → published → rescan) and a follow-up scan, so you can show whether the work actually moved the metric.
Built for agencies and in-house teams
Agencies run each client as its own project with its own prompts, competitors and market, and share a read-only report per client. In-house teams use the same workspace to watch one brand deeply. Pricing is credit-based and public: 1 credit = 1 prompt × engine × geo × sample, so cost is legible rather than a black box.
Related
FAQ
What is an AI visibility platform?
Software that measures whether AI assistants (ChatGPT, Gemini, Perplexity, Google AI Overviews) mention, cite or recommend your brand for real questions, and helps you improve that presence. Answerly adds sample size, margin of error and the raw answers behind every metric.
Which AI engines does Answerly track?
ChatGPT, Gemini, Perplexity and Google AI Overviews (Google AI Mode is in progress). Support for a new surface is only claimed once it is actually implemented — we do not list engines we cannot measure.
Is this the same as SEO rank tracking?
No. There is no single "position" in an AI answer. Answerly measures mention rate, citation rate and share of voice per engine, with stated uncertainty — not a keyword rank.
How is Answerly different from other AI visibility tools?
Repeated sampling with visible sample size and margin of error, mention separated from citation, raw evidence for every result, prompt-level competitor gaps, Search Console-grounded prompt discovery, and an action plan — not just a score.
Can I see the actual AI answer behind a metric?
Yes. Every recorded mention and citation links to the captured dialogue with its engine and date, and that snapshot can be shared as a prooflink.
How much does it cost?
There is a free trial with no card. Paid plans are credit-based and public: 1 credit = 1 prompt × engine × geo × sample.
See if AI recommends your brand
Start free — no card. Run your first AI visibility check across ChatGPT, Gemini and Perplexity.