Weak AI visibility with 2 of 22 criteria passing. Biggest gap: llms.txt file.
Verdict
allus.ai currently has low AEO readiness (overall score: 15) because core machine-readable discovery signals are missing despite strong visible content volume. The site has substantial crawlable text (12,637 characters), HTTPS, and solid fact density (9 quantitative data points), but foundational files and markup are absent: `llms.txt` (404), `robots.txt` (404), `sitemap.xml` (404), and all JSON-LD schema blocks (0). Content is also hard for answer engines to extract due to no Q&A headings, no direct-answer patterns, no lists/tables, and only 1 internal link. In short, the site has raw material, but lacks the technical packaging AI engines need for reliable citation.
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.
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.
No date on your page? AI engines treat it like a rumor -undated and deprioritized. Here's how we audit whether your timestamps are actually machine-readable.
Want us to improve your score?
We build citation-ready content that AI engines choose as the answer.