Weak AI visibility with 1 of 22 criteria passing. Biggest gap: llms.txt file.
Verdict
atlasgrid.ai has a strong technical baseline for crawlability (HTTPS enabled, substantial on-page text, and semantic elements like <main> and <section>), but it is currently not AEO-ready. Core machine-readable discovery assets are missing: /llms.txt, /robots.txt, /sitemap.xml, and homepage JSON-LD are all absent (HTTP 404 or zero detected blocks). The site also lacks extractable answer structure (0 question headings, 0 direct Q&A patterns, no H1, no FAQ page) and trust reinforcement signals (no Organization/Person schema, no quantitative facts, no freshness metadata). In practice, AI engines can access the page, but have very little structured evidence to confidently interpret, rank, and cite it.
Scoreboard
Top Opportunities
Improve Your Score
Guides for the criteria with the most room for improvement
Tidio has a 251-line llms.txt. Crisp has zero. The score gap: +29 points. This single file tells AI assistants exactly what your site does -and without it, they're guessing.
Tidio runs 4 JSON-LD schema types. Crisp runs zero. That's not a coincidence -it's the difference between a 63 and a 34. Structured data is the machine-readable layer AI trusts most.
AI assistants are question-answering machines. When your content is already shaped as questions and answers, you're handing AI a pre-formatted citation. Sites that do this right get extracted -sites that don't get skipped.
Our site runs 87 FAQ items across 9 categories with FAQPage schema on every one. That's not excessive -it's how we hit 88/100. Each Q&A pair is a citation opportunity AI can extract in seconds.
Want us to improve your score?
We build citation-ready content that AI engines choose as the answer.