Why AI visibility needs its own audit
Traditional SEO tells you whether a page can be crawled and ranked. AI visibility asks a different question: can an answer engine confidently understand, cite, and recommend your company?
For technical companies, this depends on entity clarity, topical depth, structured data, and proof that your services solve specific problems.
Entity signals to verify
- Organization name and canonical domain
- Primary services and industries
- Location coverage
- Author and reviewer signals
- Case studies, resources, and supporting pages
Content cluster checks
Each article should support a clear topic cluster. For OrcaTech, the most important clusters are cybersecurity, AI security, GEO, web development, automation, and digital transformation.
| Signal | What to Review |
|---|---|
| Depth | Does the article answer follow-up questions? |
| Citability | Can another source quote a concise claim? |
| Internal links | Does the article connect to services and related resources? |
Technical checks
const requiredSignals = [
"canonical",
"hreflang",
"Article schema",
"BlogPosting schema",
"RSS inclusion",
"sitemap inclusion",
];
AI systems reward clarity. The easier your content is to parse, the easier it is to cite.
Recommended next step
Run a quarterly AI visibility audit and update the topic clusters that support your highest-value services.
