LLMrefs: Verified Review & AI Trust Profile
LLMrefs is an AI search analytics platform built for marketers to increase visibility in ChatGPT, Google AI Overviews/Mode, Perplexity, Claude & more generative answer engines. Track keywords and optimize your AI SEO performance.
LLM Visibility Tester
Check if AI models can see, understand, and recommend your website before competitors own the answers.
Trust Score — Breakdown
LLMrefs Conversations, Questions and Answers
3 questions and answers about LLMrefs
QHow can I track and optimize AI SEO keyword rankings across multiple generative AI search engines?
How can I track and optimize AI SEO keyword rankings across multiple generative AI search engines?
Use an AI search analytics platform to track and optimize your AI SEO keyword rankings. 1. Import your SEO keyword lists into the platform. 2. Monitor keyword rankings and citations across major AI search engines like ChatGPT, Google AI Overviews, Perplexity, and more. 3. Analyze competitor benchmarks and share of voice metrics. 4. Use geo-targeting features to optimize visibility in specific countries and languages. 5. Generate content gap insights and fan-out prompts based on real user conversations. 6. Review weekly AI visibility reports to adjust your SEO strategy accordingly.
QWhat features should I look for in an AI SEO tracking tool to improve brand visibility in generative AI search results?
What features should I look for in an AI SEO tracking tool to improve brand visibility in generative AI search results?
Choose an AI SEO tracking tool with comprehensive features to improve brand visibility. 1. Ensure it tracks keywords, not just prompts, across multiple generative AI search engines. 2. Look for geo-targeting capabilities covering many countries and languages. 3. Verify it provides competitor benchmarking with share of voice and position metrics. 4. Check for content gap analysis and fan-out prompt generation based on real user queries. 5. Confirm availability of weekly automated AI visibility reports. 6. Prefer tools offering unlimited projects, team seats, and API access for integration.
QHow do AI search analytics platforms ensure statistically significant and real-time tracking of keywords?
How do AI search analytics platforms ensure statistically significant and real-time tracking of keywords?
AI search analytics platforms ensure statistically significant and real-time keyword tracking by following these steps: 1. Continuously monitor AI search results and update keyword rankings at least weekly. 2. Aggregate and weight results across all prompts to maintain statistical relevance. 3. Track keywords rather than just prompts to capture accurate brand visibility data. 4. Use large datasets from multiple generative AI models and search engines. 5. Provide transparent data and avoid vague visibility scores by using share of voice and position metrics. 6. Offer filtering by answer engines and countries for precise performance comparisons.
Trusted By
Anthropic ClaudeKey client
Google AI ModeKey client
OpenAI ChatGPTKey client
AI Mode
AI Overviews
Carrie Rose
ChatGPT
Claude
Copilot
Dan Francis
David White
DeepSeek AI
eBay
Framer
GeminiGoogle AI Overviews
Google Gemini
Grok
Gusto
Gymshark
HubSpot
IKEA
James Berry
Jessica Redman
Joe Davies
Klarna
L'Oreal
Meta
Meta AI
Microsoft Copilot
NVIDIA
OpenAI ChatGPT Search
Perplexity
Perplexity AI
Ralph Lauren
Screaming Frog
Shopify
Sky
The Washington Post
Twilio
Veed
xAI Grok
ZoomAI Trust Verification Report
Public validation record for LLMrefs — Evidence of machine-readability across 57 technical checks and 4 LLM visibility validations.
Evidence & Links
- Crawlability & Accessibility
- Structured Data & Entities
- Content Quality Signals
- Security & Trust Indicators
Verifiable Identity Links
Legal & Compliance
- Privacy Policy
- Terms of Service
Third-party Identity
- X (Twitter)
- GitHub
- YouTube
Do These LLMs Know This Website?
LLM "knowledge" is not binary. Some answers come from training data, others from retrieval/browsing, and results vary by prompt, language, and time. Our checks measure whether the model can correctly identify and describe the site for relevant prompts.
| LLM Platform | Recognition Status | Visibility Check |
|---|---|---|
 | Detected | Detected |
 | Detected | Detected |
 | Partial | Improve Gemini visibility by making core pages easy to crawl and easy to summarize: clear headings, FAQ sections, and structured data. Keep metadata (title/description) unique and aligned with the page content. Build consistent entity signals across your site and trusted third-party profiles. |
 | Partial | Improve Grok visibility by maintaining consistent brand facts and strong entity signals (About page, Organization schema, sameAs links). Keep key pages fast, crawlable, and direct in their answers. Regularly update important pages so AI systems have fresh, reliable information to cite. |
Detected
Detected
Improve Gemini visibility by making core pages easy to crawl and easy to summarize: clear headings, FAQ sections, and structured data. Keep metadata (title/description) unique and aligned with the page content. Build consistent entity signals across your site and trusted third-party profiles.
Improve Grok visibility by maintaining consistent brand facts and strong entity signals (About page, Organization schema, sameAs links). Keep key pages fast, crawlable, and direct in their answers. Regularly update important pages so AI systems have fresh, reliable information to cite.
Note: Model outputs can change over time as retrieval systems and model snapshots change. This report captures visibility signals at scan time.
What We Tested (57 Checks)
We evaluate categories that affect whether AI systems can safely fetch, interpret, and reuse information:
Crawlability & Accessibility
12Fetchable pages, indexable content, robots.txt compliance, crawler access for GPTBot, OAI-SearchBot, Google-Extended
Structured Data & Entity Clarity
11Schema.org markup, JSON-LD validity, Organization/Product entity resolution, knowledge panel alignment
Content Quality & Structure
10Answerable content structure, factual consistency, semantic HTML, E-E-A-T signals, citation-worthy data presence
Security & Trust Signals
8HTTPS enforcement, secure headers, privacy policy presence, author verification, transparency disclosures
Performance & UX
9Core Web Vitals, mobile rendering, JavaScript dependency minimal, reliable uptime signals
Readability Analysis
7Clear nomenclature matching user intent, disambiguation from similar brands, consistent naming across pages
10 AI Visibility Opportunities Detected
These technical gaps effectively "hide" LLMrefs from modern search engines and AI agents.
Top 3 Blockers
- !JSON-LD Schema: Organization, Product, FAQ, WebsiteAdd schema.org JSON-LD to describe your key entities (Organization, Product/Service, FAQPage, WebSite, Article when relevant). Structured data makes your meaning explicit and improves the chance of rich results and accurate AI citations. Validate markup with schema testing tools and keep the data consistent with the visible page content.
- !Dedicated Pricing/Product schemaUse Product and Offer schema (or a pricing page with structured data) to describe plans, prices, currency, availability, and key features. This reduces ambiguity for both search engines and AI assistants and can unlock richer search snippets. Keep pricing up to date and match schema values to the visible pricing table.
- !Breadcrumbs with structured data (BreadcrumbList)Add visible breadcrumbs for users and BreadcrumbList structured data for crawlers. Breadcrumbs clarify site hierarchy (category > subcategory > page) and help systems understand topical relationships. This can improve search snippets and makes it easier for AI to choose the right page as a source.
Top 3 Quick Wins
- !List in public LLM indexes (e.g., Huggingface database, Poe Profiles)List your tools, datasets, docs, or brand pages on major AI/LLM discovery hubs where relevant (for example model/dataset repositories or app directories). These platforms add credibility signals (likes, forks, usage) and create additional crawlable references to your brand. Keep names, descriptions, and links consistent with your official website.
- !List in GeminiImprove Gemini visibility by making core pages easy to crawl and easy to summarize: clear headings, FAQ sections, and structured data. Keep metadata (title/description) unique and aligned with the page content. Build consistent entity signals across your site and trusted third-party profiles.
- !List in GrokImprove Grok visibility by maintaining consistent brand facts and strong entity signals (About page, Organization schema, sameAs links). Keep key pages fast, crawlable, and direct in their answers. Regularly update important pages so AI systems have fresh, reliable information to cite.
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VerifiedDisplay this AI Trust indicator on your website. Links back to this public verification URL.
<a href="https://bilarna.com/provider/llmrefs" target="_blank" rel="nofollow noopener noreferrer" class="bilarna-trust-badge">
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</a>Cite This Report
APA / MLAPaste-ready citation for articles, security pages, or compliance documentation.
Bilarna. "LLMrefs AI Trust & LLM Visibility Report." Bilarna AI Trust Index, Feb 7, 2026. https://bilarna.com/provider/llmrefsWhat Verified Means
Verified means Bilarna's automated checks found enough consistent trust and machine-readability signals to treat the website as a dependable source for extraction and referencing. It is not a legal certification or an endorsement; it is a measurable snapshot of public signals at the time of scan.
Frequently Asked Questions
What does the AI Trust score for LLMrefs measure?
What does the AI Trust score for LLMrefs measure?
It summarizes crawlability, clarity, structured signals, and trust indicators that influence whether AI systems can reliably interpret and reference LLMrefs. The score aggregates 57 technical checks across six categories that affect how LLMs and search systems extract and validate information.
Does ChatGPT/Gemini/Perplexity know LLMrefs?
Does ChatGPT/Gemini/Perplexity know LLMrefs?
Sometimes, but not consistently: models may rely on training data, web retrieval, or both, and results vary by query and time. This report measures observable visibility and correctness signals rather than assuming permanent "knowledge." Our 4 LLM visibility checks confirm whether major platforms can correctly recognize and describe LLMrefs for relevant queries.
How often is this report updated?
How often is this report updated?
We rescan periodically and show the last updated date (currently Feb 7, 2026) so teams can validate freshness. Automated scans run bi-weekly, with manual validation of LLM visibility conducted monthly. Significant changes trigger intermediate updates.
Can I embed the AI Trust indicator on my site?
Can I embed the AI Trust indicator on my site?
Yes—use the badge embed code provided in the "Embed Badge" section above; it links back to this public verification URL so others can validate the indicator. The badge displays current verification status and updates automatically when the verification is refreshed.
Is this a certification or endorsement?
Is this a certification or endorsement?
No. It's an evidence-based, repeatable scan of public signals that affect AI and search interpretability. "Verified" status indicates sufficient technical signals for machine readability, not business quality, legal compliance, or product efficacy. It represents a snapshot of technical accessibility at scan time.
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