Weak AI visibility with 10 of 22 criteria passing. Biggest gap: q&a content format.
Verdict
vetrec.io has a solid technical base for AI discovery, but low extractability keeps its overall AEO score at 42/100. Core machine-readable signals are strong (llms.txt 10/10, Schema.org 10/10, canonical strategy 10/10, sitemap completeness 8/10), so the site is index-ready. However, answer formatting and crawl ergonomics are underdeveloped: Q&A content format is 0/10, internal linking is 0/10, table/list extractability is 0/10, and RSS/Atom is 0/10. The biggest gains now come from converting existing content into structured, answer-first, citation-friendly blocks and strengthening on-page semantic navigation.
Scoreboard
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Guides for the criteria with the most room for improvement
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.
AI has a trust hierarchy for sources. At the top: proprietary data and first-hand expert analysis. At the bottom: rewritten Wikipedia articles. We've watched AI preferentially cite sites with original benchmarks -even over bigger competitors.
AI crawlers follow internal links to discover and contextualize content. A page with zero inbound links is a page AI will never find. Hub pages linking to 20+ related articles signal topical authority that both engines reward.
Sitemaps tell crawlers what exists. RSS feeds tell them what changed. If you don't have one, your new content waits days -or weeks -to be discovered.
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We build citation-ready content that AI engines choose as the answer.