Free Tool
Free AI Search Visibility Checker
AI answer mention: Whether the model includes your brand in an AI visibility answer.
Platform evidence: Which configured answer surfaces were checked in this preview run.
Citation signals: Owned, third-party, review, documentation, and unverified source patterns.
Visibility opportunities: Specific fixes to improve future AI answers and source trust.
Use the score, sources, named entities, and opportunities below to decide what to clarify before creating a recurring monitor.
Get an AI visibility read in three steps.
The free checker gives a first-pass report for one AI visibility prompt. Saved monitors turn the same evidence model into recurring prompt tracking, entity context, and stakeholder-ready reports.
Enter your domain
Add a brand domain or website URL so the checker can infer the brand and canonical host.
Click Check Visibility
Run the AI visibility prompt against configured answer surfaces and extract mention, citation, sentiment, and source signals.
Review the report
Use the score, sources, responses, entity context, and opportunities to decide what to improve next.
Understand whether AI Search has enough evidence to mention your brand.
AI brand visibility is not a single ranking. It is the pattern of where your company appears in ChatGPT, Claude, Gemini, Perplexity, and other AI platforms, which related entities are named, what sources are cited, and whether the answer describes your category, audience, and value correctly.
This free checker gives you a practical first pass. It creates prompts you can test in answer engines and highlights the source hygiene questions to review before moving into recurring AI Search monitoring.
AI Search prompt coverage
Build category, recommendation, source-hygiene, and evidence prompts around the way people ask ChatGPT, Claude, Gemini, Perplexity, Grok, and other AI platforms for answers.
Canonical source hygiene
Check whether your owned domain, product pages, docs, reviews, and reference content give AI responses enough reliable context to cite.
Entity context
Look for prompts where other named entities, sources, or categories appear before your brand is clearly explained.
Content AI can cite
Turn missing mentions into practical work: stronger FAQs, canonical pages, llms.txt updates, source cleanup, briefs, and citation outreach.
Report contents
What is in your AI search grade report?
The report connects the score to the actual evidence: mentions, platform coverage, sources, entity context, prompts, response snapshots, volume context, and opportunities.
AI Visibility Score
A score out of 100 that summarizes brand presence, answer position, citation evidence, sentiment, and competitor pressure.
Mentions
The total number of times your brand is named in AI-generated answers across monitored prompts.
Platform Coverage
Which AI answer surfaces mention the brand and how often each platform includes it.
Sources
Unique cited URLs and domains that shape answers mentioning your brand, products, services, or competitors.
Top Industry Sources
The recurring third-party, owned, review, community, and directory sources AI systems use for the category.
Competitor Visibility
A side-by-side view of competitor mentions, answer share, position, and estimated prompt pressure.
Prompts
The real buyer questions that trigger mentions, misses, citations, and competitor recommendations.
Volume
Search-demand context for the keyword behind each prompt, available in saved reports when demand data exists.
LLM Responses
The actual answer snapshots showing how AI systems describe your brand and compare it with competitors.
Opportunities
High-impact prompt and source gaps where competitors appear, citations are weak, or brand context is missing.
Geo Distribution
Country-level breakdown of brand mentions showing where global AI visibility is strongest and where geographic gaps exist.
Narrative Drivers
Top cited domains and prompt drivers shaping the brand story, with sentiment trend analysis over time.
Prompt Gaps
Prompts where competitors appear but the brand does not, or where brand position is weak compared to alternatives.
Cited Domains
The specific domains AI platforms reference most when mentioning the brand, revealing influential sources for outreach.
Cited Pages
The exact URLs most frequently cited alongside the brand, showing which pages shape how AI talks about the brand.
Interpret the score
Use the score as a roadmap, not a vanity metric.
A high score means AI answers have clearer evidence for your brand. A low score shows where weak sources or unclear context are shaping the answer before your brand appears.
High score
Protect the prompts and sources already driving visibility. Refresh cited pages, expand proven topics, and keep third-party proof current.
Low score
Start with prompts where competitors appear but your brand does not. Build direct answer pages, comparison coverage, and better source proof.
Weak sources
Strengthen the pages AI systems already cite. Add clearer product facts, reviews, case studies, docs, and canonical source guidance.
Negative or neutral context
Give answer engines better evidence by adding customer proof, category positioning, implementation details, and current product claims.
Manual workflow
Check AI Search visibility by following the answer, not just the brand mention.
Start with visibility prompts
Do not only ask an AI tool to summarize your homepage. Test category, recommendation, pricing, problem-aware, citation, and source-trust prompts.
Capture the full answer
Record whether your brand appears, where it appears, which related entities are named, what sentiment is implied, and which sources are cited.
Separate owned and third-party sources
Owned pages show whether your site explains the product clearly. Third-party sources show whether the market has enough external confirmation.
Map every miss to a fix
A weak answer should become a content, source, schema, llms.txt, review, or canonical-page task rather than a vague visibility score.
Improve the next answer
Turn weak AI Search visibility into specific content and source fixes.
A useful checker should not stop at a score. The output should tell your SEO, brand, and growth teams which evidence is missing, which sources AI used, and which pages can improve the next generated answer.
A one-time check is enough to find obvious gaps. Recurring monitoring matters when the same prompt clusters influence pipeline, client reporting, content priorities, or executive visibility metrics.
Move to scheduled scans when you need prompt history, answer snapshots, source classification, entity movement, and reports that show what changed over time.
Explore recurring monitoringGEO workflow
Improve AI search visibility with repeatable GEO actions.
Generative Engine Optimization works best when prompt gaps, citations, and answer wording become a recurring content and source-quality backlog.
Close visibility gaps with competitors
Identify prompts where competitors appear but your brand does not, then publish content that answers the same buying question directly.
Strengthen citation sources
Improve owned pages and earn mentions from the authoritative sources AI systems already draw from in your category.
Optimize positive positioning
Back up product claims with reviews, case studies, comparisons, and expert content so AI responses have stronger material to reference.
Focus on high-impact prompts
Prioritize prompt clusters with buyer intent and meaningful demand instead of chasing every possible brand mention.
Track progress across platforms
Compare ChatGPT, Gemini, Perplexity, Google AI, and other answer surfaces so platform-specific blind spots do not hide.
Use reports as a GEO roadmap
Treat every report as a backlog of prompt, source, crawler, comparison, and content improvements.
Keep the visibility workflow connected.
Use these public resources to move from a first check to better prompts, cleaner canonical sources, and a repeatable AI search visibility workflow.
ChatGPT Query Generator
Create more prompt variations for category, recommendation, and source-trust checks.
llms.txt Generator
Draft machine-readable guidance that points AI systems to canonical product sources.
AI Visibility Tools Comparison
Evaluate recurring monitoring platforms by prompt outcome, citations, and action workflows.
Platform Features
See how scheduled scans, source analytics, crawler signals, briefs, and reports work together.
FAQ
What is AI brand visibility?
AI brand visibility is whether answer engines such as ChatGPT, Gemini, Perplexity, Claude, and AI overview-style results can understand, mention, cite, and recommend your brand for relevant prompts.
How do I check if ChatGPT mentions my brand?
Run AI visibility prompts around your domain, category, citations, source trust, and positioning. Then record whether your brand appears, which entities appear with it, and which sources shape the answer.
What sources influence AI brand recommendations?
Owned product pages, documentation, pricing pages, reference pages, review sites, listicles, forums, videos, news, partner pages, and social proof can all influence how AI systems describe a brand.
How often should I check AI visibility?
A first manual check is useful for a baseline. Teams that depend on AI search for discovery should recheck important prompt groups weekly or monthly so changes in mentions, citations, and source context are visible.
What should I do if other entities appear but my brand does not?
Find the missing evidence behind the answer. Usually the fix is clearer category copy, stronger source coverage, better third-party proof, stronger FAQs, canonical source cleanup, or recurring monitoring across the prompts that matter.
Show the same product truth to crawlers, AI systems, and evaluators.
Competitive AI visibility products expose public discovery files, evidence-led docs, and a transparent self-check path. prompts-gpt.com should do the same so the market sees the current AI visibility platform, not older prompt-library snapshots or a rerun URL without context.
Use the live checker for diagnostics. Use the published markdown or JSON self-audit exports when you need a stable public proof artifact. The JSON export also includes the Prompts-GPT.com project preset and monitor blueprint used for the ongoing internal follow-up path.
llms.txt
Machine-readable source map for the current product truth.
robots.txt
Crawler access policy for public and private routes.
sitemap.xml
Canonical public URL inventory for discovery and recrawl.
Self-audit export
Stable markdown proof artifact for the prompts-gpt.com self-evaluation.
Self-audit JSON
Machine-readable self-audit payload with credibility notes and project guidance.
Self-audit report
Public methodology, export guidance, and current discovery gaps.
Live checker rerun
Fresh diagnostic surface for answer snapshots, citations, and recommendations.
Make each share surface explicit about stability, format, and audience.
The self-test showed that public discovery surfaces are only credible when buyers can tell which link is stable proof, which one is a live rerun, which files are AI-readable discovery aids, and which path requires sign-in for recurring monitoring.
Self-audit markdown export
markdownStable proofStable public proof artifact for external sharing, procurement review, and citations.
Audience: buyer
Open Self-audit markdown export: /reports/prompts-gpt-com-self-audit.mdSelf-audit JSON export
jsonStable proofMachine-readable self-audit payload with credibility notes, export context, and project guidance.
Audience: ai-system
Open Self-audit JSON export: /reports/prompts-gpt-com-self-audit.jsonSelf-audit article
htmlStable proofMethodology, current limits, and product-claim boundaries for public evaluation.
Audience: buyer
Open Self-audit article: /articles/prompts-gpt-com-ai-visibility-self-auditFree checker rerun URL
htmlLive diagnosticFresh answer snapshot, source list, and recommendations for live inspection.
Audience: operator
Open Free checker rerun URL: /free-tools/ai-brand-visibility-checker?site=prompts-gpt.com&submitted=1Official llms.txt
txtAI-readableCanonical AI-readable source map for the current public product story.
Audience: ai-system
Open Official llms.txt: /llms.txtrobots.txt
txtAI-readableCrawler access policy for public versus private routes.
Audience: crawler
Open robots.txt: /robots.txtsitemap.xml
xmlAI-readableCanonical public URL inventory for discovery and recrawl.
Audience: crawler
Open sitemap.xml: /sitemap.xmlPrompts-GPT.com project preset
htmlProject handoffAuthenticated handoff path from one public self-check into recurring monitoring.
Audience: operator
Open Prompts-GPT.com project preset: /free-tools/ai-brand-visibility-checker?auth=sign-up&next=%2Fdashboard%2Fprojects%2Fnew%3Fbrand%3DPrompts-GPT.com%26site%3Dhttps%253A%252F%252Fprompts-gpt.com%26category%3DAI%2Bsearch%2Bvisibility%2Bplatform%26source%3Dfree-checkerMake the public proof boundary explicit for every credibility check.
The self-audit should not force evaluators to infer which parts are inspectable now, which are only directional, which require a saved monitor, and which require sign-in. The matrix below makes that boundary machine-readable and visible on the page.
Answer snapshots
Inspectable nowA credible AI visibility product should show the actual answer snippet instead of summarizing results as a score only.
Inspect by
Run the checker on prompts-gpt.com, read the answer snippet and full-answer evidence, then preserve that run with the checker markdown or JSON download.
Share policy
Use checker-run markdown or JSON when sharing one diagnostic run. Use the self-audit export and article for durable product-level proof.
Citations and source evidence
Inspectable nowBuyers need to see whether owned pages, third-party reviews, or comparison pages are actually supporting the answer.
Inspect by
Inspect detected source URLs, provider-verified flags, top industry sources, and source labels in the live checker result or the checker-run exports.
Share policy
Treat citation lists from one checker run as directional evidence. Use the self-audit export to explain what the product can prove publicly today.
Recommendations
Inspectable nowDiscovery tooling is only useful when the answer evidence turns into concrete next actions instead of a generic score.
Inspect by
Review the checker recommendations below the answer snapshot and compare them with the documented workflow in the public docs.
Share policy
Recommendations from one run are acceptable to share as tactical diagnostics, but not as recurring trend proof.
Opportunity backlog
Inspectable nowOperators need a clear backlog that connects missing mentions or weak citations to pages, briefs, FAQs, or source fixes.
Inspect by
Inspect the opportunity cards and exported opportunity payload from the live checker run for prompts-gpt.com.
Share policy
Use checker-run exports for run-specific opportunities. Use the self-audit export to explain the proof boundary between one run and recurring monitoring.
Scoring and confidence
Directional onlySingle-run scores are easy to overclaim. Public proof should state that a preview score is directional until repeated prompt tracking exists.
Inspect by
Compare the preview score against the benchmark prompt pack and the scoring limitation notes before treating it as a durable benchmark.
Share policy
Do not use a single rerun score as a long-term performance claim. Use repeated monitoring for trend or share-of-voice claims.
Crawler-to-citation logic
Monitor onlyConnecting crawler events to later citations is valuable, but the free checker should not imply that capability without a saved monitor.
Inspect by
Review the public feature and docs pages for the workflow description, then confirm the actual crawler-to-citation evidence only inside a saved monitor.
Share policy
Keep crawler-to-citation claims at the workflow and methodology level in public materials. Do not present them as checker output.
Project guidance and recurring setup
Requires authA public self-check should hand off cleanly into a real recurring project when the platform's own prompt set is worth monitoring.
Inspect by
Use the built-in Prompts-GPT.com project preset and baseline monitor prompts after sign-in, then rerun the benchmark prompt pack as a saved project.
Share policy
Public proof can link to the authenticated handoff path, but project creation and recurring monitor evidence remain account-bound.
A credible self-test needs more than one branded rerun prompt.
The branded checker prompt is useful for a first-pass diagnostic, but recurring self-evaluation should also test category, competitor, recommendation, local, and buying-intent prompts. Those benchmark prompts are exported with the self-audit so the proof path stays reproducible.
Analyze AI visibility for prompts-gpt.com. Is the brand understood, mentioned, cited, and positioned accurately in AI answers?
diagnosticUseful as a first-pass branded diagnostic, but still biased because the prompt names the brand directly.
best AI search visibility platforms for marketing teams
categoryExpands self-evaluation beyond the branded diagnostic into category-level AI visibility prompts.
tools for monitoring brand visibility in ChatGPT and Perplexity
categoryExpands self-evaluation beyond the branded diagnostic into category-level AI visibility prompts.
prompts-gpt.com alternatives for AI visibility monitoring
competitorChecks whether prompts-gpt.com is explainable in comparison and alternative workflows instead of only branded prompts.
prompts-gpt.com vs PromptWatch for answer engine optimization
competitorChecks whether prompts-gpt.com is explainable in comparison and alternative workflows instead of only branded prompts.
which AI visibility tools should an SEO agency compare
recommendationTests whether the platform appears in shortlist and buyer-guidance prompts where evaluators expect independent recommendations.
recommend software for tracking AI answer citations and brand mentions
recommendationTests whether the platform appears in shortlist and buyer-guidance prompts where evaluators expect independent recommendations.
AI search visibility tools for teams in the United States
localVerifies whether region-specific discovery claims hold outside the core branded story.
AI visibility software pricing and features for a growing brand
buying_intentChecks whether pricing and feature pages support commercial AI answers with enough proof.
which AI brand monitoring platform should I buy
buying_intentChecks whether pricing and feature pages support commercial AI answers with enough proof.
Public AI visibility products are judged on proof, not only feature copy.
Competitor research consistently raises the same bar: exportable evidence, shareable reporting, public methodology, and a clean handoff into recurring monitoring. This kit exists so prompts-gpt.com reads like an AI Search visibility platform rather than a generic dashboard with AI-themed marketing.
Stable public proof export
supported publiclyBuyers need a shareable artifact that does not mutate when answer providers change.
Machine-readable evidence export
supported publiclyAI systems, evaluators, and internal tools need a structured payload instead of screenshot-only proof.
Live diagnostic rerun
supported with limitsOperators need a fresh answer snapshot to inspect citations, entities, and recommendations on demand.
Public methodology and claim boundaries
supported publiclyTrust depends on explaining what scoring, citations, and crawler context can prove versus what requires saved monitoring.
Recurring reporting handoff
monitor onlyA credible platform must convert a public diagnostic into a saved project when visibility work becomes ongoing.
PDF and CSV export with citation detail
supported with limitsStakeholders expect downloadable brand reports and citation spreadsheets with full and summary modes.
Scheduled report delivery
supported with limitsRecurring automated email reports eliminate manual export steps for teams that report AI visibility to leadership.
Shareable online dashboards
monitor onlyAgencies and teams need live dashboard links that stakeholders can access without account setup.
BI connector (Looker Studio)
monitor onlyData teams need live structured feeds into existing dashboards and reporting pipelines.
Content briefs from AI insights
supported with limitsVisibility data should produce concrete content recommendations, not just metrics.
Prompt gap and competitor gap analysis
supported with limitsBuyers need to identify exactly which prompts competitors own and where the brand is absent.
Geo distribution tracking
supported with limitsGlobal brands need to understand which countries and regions provide their highest AI visibility.
Public proof expectations were checked against live category examples.
This self-audit did not invent a reporting standard. The research pass checked how adjacent AI visibility products explain citations, documentation, and exports in public before setting the proof policy for prompts-gpt.com.
Semrush AI Visibility Toolkit
Recurring reporting, prompt research, and shareable AI visibility dashboardsReviewed 2026-05-16Semrush publicly documents prompt research, visibility overview, brand performance reporting, PDF exports, CSV exports, and shareable online dashboards inside the AI Visibility Toolkit.
Why it matters: Buyers now expect AI visibility tools to move from one-off scans into recurring reporting and stakeholder-ready sharing.
Semrush KB - Getting Started with the AI Visibility ToolkitPeec AI
AI search analytics, source influence metrics, and BI-friendly reportingReviewed 2026-05-16Peec documents visibility, position, sentiment, source-used metrics, a documentation llms.txt index, and a Looker Studio connector for reporting.
Why it matters: Clear metric definitions, machine-readable docs, and reporting connectors make public product claims easier to trust.
Peec AI Docs - Welcome and Looker Studio connectorProfound
Answer-engine tracking plus actions and query fanout analysisReviewed 2026-05-16Profound publicly documents visibility tracking across major answer engines, query fanouts, actions, and customer workflows tied to AI search outcomes.
Why it matters: Public product stories in this category increasingly connect measurement to concrete action workflows instead of isolated scoring.
Profound - Introducing Actions and Query FanoutsScrunch
Citation drill-down and source-level influence reviewReviewed 2026-05-16Scrunch publicly documents citation grouping by domain or URL, platform filtering, and citation-level influence analysis in its help center.
Why it matters: Answer evidence without source drill-down is weak; buyers want to inspect which domains influence mentions and citations.
Scrunch Help Center - Understanding the Citations Tab in ScrunchOtterlyAI
Export-oriented reporting and GEO audit artifactsReviewed 2026-05-16Otterly publicly documents CSV exports for prompts and citations, a GEO Audit PDF export, a Looker Studio connector, and explicit boundaries for what is not exportable yet.
Why it matters: Claim boundaries matter in this category; precise public export disclosures are more trustworthy than broad unsupported promises.
Otterly Help - Can I export my data and reports?Ahrefs Brand Radar
Search-backed prompt database with free AI visibility checker and cited domain analysisReviewed 2026-05-16Ahrefs publicly provides a free no-signup AI visibility checker with mentions by platform, top 5 topics, top 5 cited domains, and top 5 cited pages. Brand Radar tracks 400M+ monthly search-backed prompts derived from real search behavior across ChatGPT, Gemini, Perplexity, Copilot, AI Overviews, AI Mode, and Grok.
Why it matters: A free checker with no signup creates a strong top-of-funnel acquisition loop. Search-backed prompts from real user behavior are more trustworthy than synthetic question sets. Cited domain and cited page analysis gives actionable source intelligence.
Ahrefs - Free AI Visibility Checker and Brand RadarPublic proof should include what is still weak.
A credible AI visibility platform should publish risks discovered during self-testing, not only positive feature claims. These risks are mirrored in the self-audit markdown and JSON exports for external review.
Legacy prompt-library snippets still outrank AI visibility positioning for some queries
highEvidence: Public search results still surface the /prompts listing with a legacy 'Best AI Prompts Library' snippet while the homepage describes prompts-gpt.com as an AI visibility platform.
Impact: Evaluators can misclassify prompts-gpt.com as a generic prompt library instead of an AI Search Visibility platform.
Action: Keep /, /features, /pricing, /resources, /docs, /articles, and self-audit exports internally consistent; keep canonical AI visibility positioning in llms.txt and avoid reintroducing prompt-library-first metadata.
Live rerun links are easy to treat as permanent proof
mediumEvidence: The free checker URL is public and shareable, but the output can change as providers, citations, and model behavior shift.
Impact: External stakeholders may treat mutable diagnostics as stable evidence and misread score changes as regressions.
Action: Use markdown/JSON exports and the self-audit article as the default proof artifacts in public sharing and documentation.