Weak AI visibility with 5 of 22 criteria passing. Biggest gap: llms.txt file.
Verdict
vectorshift.ai currently has low AEO readiness with an overall score of 24/100, driven by foundational machine-consumption gaps rather than content volume. Core technical signals are missing, including llms.txt (0, HTTP 404), Schema.org structured data (0), RSS/Atom feed (0), and schema depth (0), which limits discoverability and extraction by AI systems. While canonical strategy is strong (10/10) and fact density is high (8/10 with 308 quantitative data points), these strengths are not packaged in formats AI agents can reliably parse and trust. In practice, the site has enough raw material, but it needs structured wrappers, attribution, and crawl directives to become answer-engine ready.
Scoreboard
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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.
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.
Your sitemap says 500 pages exist. Our crawl finds 700. Those 200 missing URLs? AI crawlers will never know they exist.
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