Weak AI visibility with 5 of 22 criteria passing. Biggest gap: llms.txt file.
Verdict
tecto.ai has a low AEO readiness profile (overall score: 18) with major machine-readability gaps despite a few foundational strengths. Critical discoverability assets are missing, including `https://tecto.ai/llms.txt` (404), JSON-LD schema (`schema_block_count: 0`), a FAQ endpoint (`/faq` returns 404), and RSS/Atom feeds. Crawl fundamentals are partially in place (`robots.txt` and sitemap both return 200, canonical is present and self-referencing), but extraction quality is weak due to `h1_count: 31`, no semantic structure (`semantic_elements_found: []`), no internal linking (`internal_link_count: 0`), and no freshness metadata (`time_element_count: 0`, `sitemap_recent_lastmod_count: 0`).
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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.
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.
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.
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