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, 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.
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.
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
Self-audit JSON export
jsonStable proofMachine-readable self-audit payload with credibility notes, export context, and project guidance.
Audience: ai-system
Self-audit article
htmlStable proofMethodology, current limits, and product-claim boundaries for public evaluation.
Audience: buyer
Free checker rerun URL
htmlLive diagnosticFresh answer snapshot, source list, and recommendations for live inspection.
Audience: operator
Official llms.txt
txtAI-readableCanonical AI-readable source map for the current public product story.
Audience: ai-system
robots.txt
txtAI-readableCrawler access policy for public versus private routes.
Audience: crawler
sitemap.xml
xmlAI-readableCanonical public URL inventory for discovery and recrawl.
Audience: crawler
Prompts-GPT.com project preset
htmlProject handoffAuthenticated handoff path from one public self-check into recurring monitoring.
Audience: operator
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.