AI Visibility Scorecard
math.group · Technology
Borderline visible. AI bots can crawl MATH Group, but the structured-data signals are thin - you are at real risk of being skipped when buyers ask ChatGPT, Claude, or Perplexity for a recommendation.
AI engines read this profile 2 times
Claude · Meta AI
#1,602,408 of 2,705,352 in Technology for AI visibility
4
AEO Visibility
iBorderline · 4.4/10
5
Muse Index Score
iAI agent readiness
Basic · 5/100
0
AI Adoption
iNone detected · 0/100
from our crawl and measurement
MATH Group describes itself simply: "Não sei qual é o meu problema Tenho pressão por resultado, mas não tenho clareza sobre a causa raiz Reduzir Custo Operacional A conta de infraestrutura, retrabalho e processos manuais." To AI engines like ChatGPT and Perplexity, though, it is barely visible: it scores 4.4 out of 10.
Under the hood there is a sitemap and a readable heading structure, but the score is capped by what is missing: structured data describing the business, an llms.txt file.
Strong · Good · Fair · Weak
Structured Data
Weak
Organization / LocalBusiness JSON-LD that AI can read.
Content Structure
Strong
Clear headings and answer-style content.
Entity Clarity
Fair
How clearly your brand identity reads to AI.
E-E-A-T Signals
Experience, Expertise, Authority, Trust
Weak
Experience, Expertise, Authority, Trust markers.
Technical AEO
Good
robots.txt, llms.txt, and AI-bot crawl access.
AI Discoverability
Good
Sitemaps and entity links AI can follow.
How the web signals your brand to AI
Backlinks
Weak
No inbound links found yet.
Domain Authority
Weak
Little domain authority yet.
Reference Presence
Weak
Not in AI knowledge graphs yet.
News & Press
Weak
No press coverage found yet.
Community
Weak
No community discussion yet.
Social Mentions
Weak
No social discussion found yet.
Your AEO score measures whether AI search engines - ChatGPT, Claude, Perplexity, Gemini - can actually read your site and cite it in answers. Roughly two-thirds of sites are invisible to them. At 4.4/10, MATH Group is crawlable but under-signaled - fixable, and the signals above are where to start.
Por que o mesmo problema tem resultados tão diferentes dependendo de quem resolve?
A resposta está em como o problema é diagnosticado. Não em qual tecnologia é aplicada. O MATH Problem-First Framework é o método que organiza todos os nossos projetos. Começa pela dor declarada, vai até a causa estrutural, mapeia o impacto no negócio e traduz tudo para uma linha que sobe ao board. Só depois disso entra a tecnologia.Os projetos que falham geralmente pulam direto para a solução.
Is this your brand?
The exact fixes for MATH Group
Which AI engines already crawl you
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The search landscape has fundamentally shifted. While Google still dominates, millions of users now ask questions to ChatGPT, Gemini, and Claude instead of typing into a search bar.
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Scored by Engagemii on August 8, 2026. Methodology: engagemii.com/aeo/methodology
Source URL: https://engagemii.com/aeo/brands/math-group
Cite this score: Engagemii (2026). "AEO Score for MATH Group." Retrieved from https://engagemii.com/aeo/brands/math-group
Licensed under CC BY 4.0. You may reuse this data with attribution: a visible link to engagemii.com.
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