Weak AI visibility with 1 of 22 criteria passing. Biggest gap: llms.txt file.
Verdict
getnivara.com currently has very low AEO readiness (overall score: 5) despite serving content over HTTPS and including a title and meta description. Core machine-readable discovery assets are missing, including `/llms.txt` (404), `/robots.txt` (404), `/sitemap.xml` (404), and all JSON-LD schema (`schema_block_count: 0`). Content is difficult for AI systems to extract and cite because there are no question headings, no direct-answer patterns, no lists/tables, no FAQ page, and zero internal links on the homepage. The biggest upside is structural: foundational technical and content primitives can be implemented quickly to materially improve crawlability, entity clarity, and citation likelihood.
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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.
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We build citation-ready content that AI engines choose as the answer.