Schema markup for AI search: the JSON-LD that helps AI describe you

Structured data won't make an AI recommend you by itself, but it removes guesswork: who the company is, what the product is called, what it costs and which profiles belong to it. AI engines that build on search indexes already parse it.

The types that matter most

• Organization: name, url, logo, sameAs (links to X, LinkedIn, GitHub, Crunchbase)
• SoftwareApplication or Product: name, description, applicationCategory, offers with price
• FAQPage: your real FAQ, matching the text on the page
• Article or BlogPosting for guides, with author and dates

Example

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@graph": [
    { "@type": "Organization", "@id": "https://acme.com/#org", "name": "Acme", "url": "https://acme.com",
      "logo": "https://acme.com/logo.png", "sameAs": ["https://x.com/acme", "https://github.com/acme"] },
    { "@type": "SoftwareApplication", "name": "Acme Analytics", "applicationCategory": "BusinessApplication",
      "description": "Privacy-friendly product analytics for SaaS teams.",
      "offers": { "@type": "Offer", "price": "0", "priceCurrency": "USD" }, "publisher": { "@id": "https://acme.com/#org" } }
  ]
}
</script>

Rules of thumb

• Only mark up what's visible on the page
• Keep names and descriptions identical across your site, directories and social profiles
• Validate with Google's Rich Results Test or the Schema.org validator