When customers ask AI,
how does your brand show up?
See what people ask and search for around your brand, and measure how search and AI answers describe you. Fill the missing questions and thin spots with evidence-based recommendations, then confirm what actually changed.
Search isn't a click anymore. It's a citation.
People read the answer AI puts together instead of picking through links one by one. If your brand isn't in that answer, customers pick someone else before they ever meet you.
- AI answers cite a handful of brands and sources. Most brands have no idea whether they're one of them.
- Getting discovered now depends on being cited in the answer, not on your rank in a list of results.
- Answers vary by engine and by question. One check can't tell you where you stand.
- That's why we don't promise you'll show up. We record what you changed and what was observed.
Find your brand's opportunities in the questions customers ask
Measure, recommend, re-check. AI search visibility handled as one continuous flow.
Keep a record of how answers describe your brand
We log mentions, rank, sentiment, and cited URLs for every engine, question, and check time. Even 'I published it, so why isn't it showing up?' gets diagnosed as a status.
- Mentions · rank · sentiment · cited URLs
- Prompt health diagnosis
- Change tracked over time
See where you stand with share of voice (SoV) in answers
See how often you and your competitors are each cited across AI engines, as a share, and pinpoint which engines and which questions you're weak on.
- Share of voice by engine
- Non-branded questions only in the denominator
- Weak engines and questions flagged
Find what's blocking you and fix it with evidence-based recommendations
We check whether AI search engines and crawlers can read your site and use it as a source. Every scored item shows which paper and which figure it rests on, graded by strength of evidence, with separate scores per engine family. Generate llms.txt and structured data, apply the fixes, then measure again.
- Three hard-gate checks
- Evidence grade on every item (12 papers)
- Scores by engine family · GEO-16 badge
- Auto-generated llms.txt and schema
- Re-measure delta to confirm the change
Map the questions customers actually ask AI
Start from a seed keyword, derive the questions customers ask, and group them by awareness, consideration, and decision stage to pick what to create next.
- Question fan-out
- Awareness · consideration · decision funnel
- Grouped into topics
Measure → Diagnose → Recommend → Publish → Confirm
Not a one-time score. A loop: change something, then check again.
- 1MeasureMeasure how you and your competitors are cited in each engine's answers.
- 2DiagnoseFind the questions you're missing and where your site is blocked, and pin down why.
- 3RecommendRecommend what to change and why, with the evidence behind it.
- 4PublishTurn recommendations into AI drafts (grounded in your brand memory and rule-checked) and structured data, then publish.
- 5ConfirmRe-measure and confirm what changed with the delta.
Here's what you'll see once you sign up
Measurements and recommendations, together in one workspace.
브랜드 가시성
마지막 스캔 오늘 09:12Screens show sample data.
If we couldn't measure it, we say so
We don't inflate numbers. We report only what we measured, what we improved, and what we observed.
Measurement integrity
- Branded questions excluded. Any question that contains the brand name is left out of the share denominator.
- Unmeasured (—) is not 0%. Not showing up and not being measured are different things.
- Prompt-set fingerprint. A change in which questions were asked is never mistaken for improvement.
Connect GA4 and GSC to see AI traffic too
Once connected, you also see site visits that started from an AI answer. Until then, we show it plainly as 'not connected' rather than guessing.
Built by a researcher
PhD candidate, Seoul National University Graduate School of AI · 1st place, CVPR 2024 AIS Challenge · ex-CERN · 7 AI and robotics patents.
We validate our method through open research
We publish explainers of the research behind AEO/GEO, starting with the original papers, and we're preparing to submit our own method as a full paper to an international peer-reviewed conference in information retrieval.
Beyond monitoring, to evidence-based action
Built for Korean search and AI answers
Naver blog SEO, Korean-language images, local platforms, and how marketing actually gets done here.AI agents can call it directly
Through our MCP server. Read tools are free; actions are billed on the same ledger as the web app.A method backed by evidence
Measurement-integrity rules and open research show the basis for every recommendation.Discover → Create → Perform
TRAIL Search, TRAIL Studio, and TRAIL Perform share the same principles.Self-serve, billed monthly
Not a months-long consulting engagement. You measure and re-measure on your own.A record, not a guarantee
Re-measure deltas and prompt health show what actually changed.An MCP server your AI agents can call directly
Read tools are free. Paid actions draw from the same credit ledger as the web app.
- Free read tools: market map, competitor SoV, visibility lookups
- Paid action tools: billed from the same ledger as the web app
- Connect directly from MCP clients like Claude and Cursor
{
"mcpServers": {
"trail-search": {
"url": "https://mcp.search.traillabs.ai/mcp"
}
}
}Start without a card. Upgrade when you need to.
Scheduled tracking doesn't use credits. Credits are spent only when you run something new, like a manual measurement, an audit, or an AI draft.
Save 17% with annual billing
1 market · 30 prompts · 120 credits/mo · 1 domain · 1 channel
Get started2 markets · 100 prompts · 500 credits/mo · 3 domains · 3 channels
Get started5 markets · 1,000 prompts · 1,400 credits/mo · 10 domains
Get startedCommon questions
Do you guarantee visibility in AI answers?+
No. We don't guarantee visibility or rankings. We measure and record what you changed and what was observed.
Which engines do you track?+
We measure answers from ChatGPT, Claude, Perplexity, Gemini, and Google AI Overview. We track the engines included in your plan on a regular schedule.
How is this different from TRAIL Studio?+
TRAIL Search is a separate product with its own subscription. TRAIL Search measures your visibility in search and AI answers, recommends what to change, and drafts the articles you're missing, grounded in your brand memory. TRAIL Studio handles creating and running visual content such as card news, video, and images.
Does scheduled tracking cost credits?+
No. Scheduled tracking doesn't use credits. Credits are spent only when you run something new: a page or site audit costs 3, a brand GEO measurement 17 (refunded when a recent tracking result is reused), an AI draft 15, question discovery 1, and a manual measurement costs prompts × engines. Failed runs are refunded automatically.
TRAIL Search and TRAIL Studio are SaaS products run by TRAIL Labs. TRAIL Perform is a planned product for ad performance analysis and budget allocation and execution.
Check your brand's AI visibility now
Start with a 10-question self-check. No card required.