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LLM Visibility Tester

Check if AI models can see, understand, and recommend your website before competitors own the answers.

Check Your Website's AI Visibility
40%
Trust Score
C
36
Checks Passed
3/4
LLM Visible

Trust Score — Breakdown

40%
LLM Visibility
3/7 passed
100%
Content
2/2 passed
29%
Crawlability and Accessibility
3/10 passed
14%
Content Quality and Structure
4/16 passed
67%
Security and Trust Signals
1/2 passed
0%
Structured Data Recommendations
0/1 passed
46%
Performance and User Experience
1/2 passed
100%
Technical
1/1 passed
27%
GEO
6/8 passed
88%
Readability Analysis
15/17 passed
Verified
36/66
3/4
View verification details

Home Conversations, Questions and Answers

3 questions and answers about Home

Q

What are common service categories for businesses and organizations?

Common service categories for businesses and organizations include retail operations like supermarkets and bookstores, real estate and property management, educational institutions such as universities, and non-profit organizations. Supermarkets and large retail stores (Super Mercados Grande) represent the consumer goods and grocery sector. Real estate encompasses both residential communities (like Palmas del Mar) and commercial property services. Educational institutions, such as the Universidad de Puerto Rico, provide academic and training services. Finally, non-profit organizations (like the Salvation Army) operate in the charitable and social services sector. Each category has distinct operational models, target audiences, and service provider needs, from supply chain software for retail to donor management systems for non-profits.

Q

How do you compare different software and service providers for a business?

To compare different software and service providers for a business, you should evaluate them based on specific criteria including core features, pricing models, scalability, vendor reputation, and integration capabilities. First, identify your business's exact needs, whether for a supermarket's inventory system, a real estate firm's CRM, or a university's learning management platform. Next, compare the core functionality each provider offers against your requirements. Examine the total cost of ownership, including subscription fees, implementation costs, and long-term maintenance. Assess the provider's reputation through customer reviews, case studies, and industry certifications. Finally, verify technical compatibility, ensuring the solution integrates with your existing tools and can scale as your organization grows. This structured approach allows for an objective comparison.

Q

What information should you prepare before requesting a quote from a service provider?

Before requesting a quote from a service provider, you should prepare detailed information about your project scope, budget constraints, technical requirements, and timeline. Start by clearly defining the project's goals and deliverables; for instance, specify if you need a point-of-sale system for a bookstore or a donor management platform for a non-profit. Outline your budget range, including any upfront investment and ongoing operational costs. Document your current technical environment, listing existing software, hardware, and any required integrations. Establish a realistic project timeline with key milestones. Additionally, have information about your team size, user roles, and any compliance needs ready. This preparation ensures the quote you receive is accurate, comparable, and tailored to your specific situation.

Services

Property Management Software

Property Management Software

View details →
AI Trust Verification

AI Trust Verification Report

Public validation record for Home — Evidence of machine-readability across 66 technical checks and 4 LLM visibility validations.

Evidence & Links

Scan Facts
Last Scan:Apr 20, 2026
Methodology:v2.2
Categories:66 checks
What We Tested
  • Crawlability & Accessibility
  • Structured Data & Entities
  • Content Quality Signals
  • Security & Trust Indicators

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.

Perplexity
Perplexity
Detected

Detected

ChatGPT
ChatGPT
Detected

Detected

Gemini
Gemini
Detected

Detected

Grok
Grok
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.

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 (66 Checks)

We evaluate categories that affect whether AI systems can safely fetch, interpret, and reuse information:

Crawlability & Accessibility

12

Fetchable pages, indexable content, robots.txt compliance, crawler access for GPTBot, OAI-SearchBot, Google-Extended

Structured Data & Entity Clarity

11

Schema.org markup, JSON-LD validity, Organization/Product entity resolution, knowledge panel alignment

Content Quality & Structure

10

Answerable content structure, factual consistency, semantic HTML, E-E-A-T signals, citation-worthy data presence

Security & Trust Signals

8

HTTPS enforcement, secure headers, privacy policy presence, author verification, transparency disclosures

Performance & UX

9

Core Web Vitals, mobile rendering, JavaScript dependency minimal, reliable uptime signals

Readability Analysis

7

Clear nomenclature matching user intent, disambiguation from similar brands, consistent naming across pages

30 AI Visibility Opportunities Detected

These technical gaps effectively "hide" Home from modern search engines and AI agents.

Top 3 Blockers

  • !
    Natural, jargon-free summary included?
    Add a short, plain-language summary near the top of the page (2–4 sentences). Avoid jargon, buzzwords, and internal acronyms; if a technical term is required, define it once in simple words. This improves readability, increases conversions, and makes the content easier for AI systems to extract and reuse in direct answers.
  • !
    Meta description present.
    Add a unique meta description on each important page that summarizes the value in 1–2 sentences. Use the main topic keyword naturally and highlight the key benefit or outcome. A strong meta description improves click-through and gives AI systems a clean summary to reference.
  • !
    Open Graph title or OpenGraph & Twitter meta tags populated
    Populate Open Graph and Twitter Card tags (og:title, og:description, og:image, og:url and their Twitter equivalents). These tags control how your pages appear when shared and are often used by crawlers to form quick summaries. Validate with social preview/debug tools to ensure the correct title, description, and image display.

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 Grok
    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.
  • !
    Does the text clearly identify common user problems or pain points and explain how the product/service solves them?
    State the user's main problem in the first 1–2 sentences, then explain exactly how your product or service solves it. Use the same wording real users use (questions, pain points, outcomes) so both search engines and AI assistants can match intent. Add quick proof (results, examples, testimonials) and a short FAQ section to make the page easy to quo…
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Embed Badge

Verified

Display this AI Trust indicator on your website. Links back to this public verification URL.

<a href="https://bilarna.com/provider/gtama" target="_blank" rel="nofollow noopener noreferrer" class="bilarna-trust-badge"> <img src="https://bilarna.com/badges/ai-trust-gtama.svg" alt="AI Trust Verified by Bilarna (36/66 checks)" width="200" height="60" loading="lazy"> </a>

Cite This Report

APA / MLA

Paste-ready citation for articles, security pages, or compliance documentation.

Bilarna. "Home AI Trust & LLM Visibility Report." Bilarna AI Trust Index, Apr 20, 2026. https://bilarna.com/provider/gtama

What 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 Home measure?

It summarizes crawlability, clarity, structured signals, and trust indicators that influence whether AI systems can reliably interpret and reference Home. The score aggregates 66 technical checks across six categories that affect how LLMs and search systems extract and validate information.

Does ChatGPT/Gemini/Perplexity know Home?

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 Home for relevant queries.

How often is this report updated?

We rescan periodically and show the last updated date (currently Apr 20, 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?

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?

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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