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Notable: Verified Review & AI Trust Profile

AI-verified business platform

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
50%
Trust Score
C
39
Checks Passed
3/4
LLM Visible

Trust Score — Breakdown

65%
LLM Visibility
5/7 passed
29%
Content
1/2 passed
79%
Crawlability and Accessibility
8/10 passed
32%
Content Quality and Structure
7/16 passed
67%
Security and Trust Signals
1/2 passed
100%
Structured Data Recommendations
1/1 passed
46%
Performance and User Experience
1/2 passed
100%
Technical
1/1 passed
27%
GEO
6/8 passed
47%
Readability Analysis
8/17 passed
Verified
39/66
3/4
View verification details

Notable Conversations, Questions and Answers

3 questions and answers about Notable

Q

What are the main types of corporate crises that businesses face?

Corporate crises encompass a range of events that threaten an organization's stability and are typically categorized into eight primary types. Economic and financial crises jeopardize solvency and liquidity, often stemming from market downturns or cash flow issues. Reputational and communicational crises arise from incidents that damage public perception, such as scandals or misinformation. Legal crises involve situations with potential lawsuits or regulatory penalties. Public affairs crises stem from political threats that hinder projects or operations. Regulatory crises occur due to changes in laws or norms affecting business practices. Internal crises include events like strikes or leadership conflicts that disrupt activities. Environmental crises are unforeseen natural or human-made disasters impacting operations. Digital crises involve leaks of sensitive private or corporate data online. Understanding these categories enables organizations to develop targeted prevention and response strategies.

Q

What is the difference between risk management and crisis management for organizations?

Risk management involves proactive measures to identify, assess, and mitigate potential threats before they escalate into crises, while crisis management focuses on reactive strategies to contain and resolve active crises to minimize damage. Risk management includes developing business continuity plans to protect people, facilities, and reputation prior to incidents, conducting diagnostic analyses for new ventures to foresee legal, political, and communicational risks, and creating corporate responsibility protocols with preventive and corrective actions. In contrast, crisis management entails immediate intervention with 360-degree mitigation plans offering legal, political, and communicational solutions tailored to specific crises, advocacy to influence public policy during disruptions, and post-crisis recovery to restore normal operations, rebuild trust, and learn from experiences. Both are integral to organizational resilience but operate at distinct stages of threat handling.

Q

How can a company protect its online reputation and personal data in a digital crisis?

A company can protect its online reputation and personal data during a digital crisis by implementing online reputation management and identity protection strategies. This involves using search engine optimization (SEO) techniques to influence Google search results and improve digital presence through innovative content, actively managing social media to shape public perception and counter misinformation. Additionally, legal measures such as blocking or suppressing disseminated data that harms privacy, honor, or image are crucial. Proactive steps include monitoring digital channels for potential threats, developing response protocols for data leaks, and engaging in digital cleaning to remove harmful content. Post-crisis, companies should assess impact, restore trust with stakeholders, and learn from incidents to enhance future performance. These combined actions help mitigate damage and ensure data security.

Services

Public Relations Services

Crisis Management Services

View details →
AI Trust Verification

AI Trust Verification Report

Public validation record for Notable — 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

27 AI Visibility Opportunities Detected

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

Top 3 Blockers

  • !
    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.
  • !
    LLM-crawlable llms.txt
    Create an llms.txt file to guide AI crawlers to your most important, high-quality pages (docs, pricing, about, key guides). Keep it short, well-structured, and focused on authoritative URLs you want cited. Treat it as a curated “AI sitemap” that improves discovery and reduces the risk of crawlers prioritizing low-value pages.
  • !
    Does page has transparent privacy & terms pages?
    Publish clear Privacy Policy and Terms pages and link them from the footer. Explain data collection, cookies, user rights, and how requests are handled (especially for regulated regions). These pages increase trust and legitimacy signals that support both SEO and AI-driven discovery.

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.
  • !
    Heading Structure
    Ensure heading levels are not skipped (e.g., H1 → H3 without H2). A proper hierarchy helps search engines and screen readers understand content structure.
Unlock 27 AI Visibility Fixes

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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/somosnotable" target="_blank" rel="nofollow noopener noreferrer" class="bilarna-trust-badge"> <img src="https://bilarna.com/badges/ai-trust-somosnotable.svg" alt="AI Trust Verified by Bilarna (39/66 checks)" width="200" height="60" loading="lazy"> </a>

Cite This Report

APA / MLA

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

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

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 Notable measure?

It summarizes crawlability, clarity, structured signals, and trust indicators that influence whether AI systems can reliably interpret and reference Notable. 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 Notable?

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 Notable 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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