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Study · 2026

The state of llms.txt & AI-citability

We scanned 57 homepages of leading SaaS and tech companies with our citability engine. llms.txt adoption has crossed the majority — but the Q&A structured data that actually gets a page quoted word-for-word is almost entirely missing.

68%

have an llms.txt file

68%

have schema.org markup

4%

have Q&A markup (FAQ/QA)

81

average citability score /100

What the leaders have — and don't

llms.txt file
68%
Schema.org (any type)
68%
Answer-ready Q&A markup
4%
Answer-ready (llms.txt + Q&A)
4%

The real gap: Q&A markup

An llms.txt helps AI read your site. But what makes them quote you word-for-word is Q&A schema.org markup (FAQPage / QAPage). Only 4% of the sites scanned have any — even among those that already have an llms.txt and generic schema. That's exactly the piece Citeable adds.

The most citable in the sample

1stripe.com100
2vercel.com100
3netlify.com100
4dropbox.com100
5asana.com100
6monday.com100
7clickup.com100
8calendly.com100

Methodology

Sample: 60 homepages of recognized SaaS / dev-tool / no-code / AI companies, scanned on 2026-07-13 (57 reachable; 3 blocked by an anti-bot firewall). Engine: the same deterministic checks as Citeable's free scan (llms.txt quality, schema.org presence, meta description, heading structure, content depth). “Q&A markup” = a FAQPage, QAPage or Question @type present in the homepage JSON-LD. Nothing is estimated: every value comes from a real crawl.

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