orbio.work — AI Search Visibility Report
Overall score: 69/100
AI search visibility analysis for orbio.work. LLMao scored orbio.work 69/100 across 8 LLM-readiness categories including crawlability, semantic content, structured data, authority signals, and answer-engine clarity.
Analyzed URL
Category breakdown
- readability: 85/100 — High clarity and professional tone. Jargon is used but generally contextualized by the 'Expertise' lists.
- schema_markup: 35/100 — Only VideoObject schema found. Missing critical Organization, WebSite, and Service schemas.
- authority_trust: 65/100 — Strong security certifications (ISO, SOC 2) but lacks individual author credentials and detailed contact info beyond a form.
- citation_sources: 40/100 — Claims are specific but lack external or internal links to supporting data/case studies. No outbound links to authoritative HR standards.
- content_freshness: 75/100 — Site is very recent (published March 2024), but lacks explicit 'last modified' dates in the visible UI or metadata.
- content_structure: 90/100 — Excellent use of H1-H3 hierarchy and semantic sections. Clear logical flow from problem to solution.
- entity_definition: 70/100 — Brand consistency is high, but lacks Person schema for founders and a dedicated glossary for AI terms.
- technical_accessibility: 80/100 — Good meta descriptions and social tags. Content is largely accessible, though Framer sites can be JS-heavy.
Top recommendations
- Implement Core Entity Schema (Schema Markup): Add Organization and Service schema to the homepage. Currently, only a VideoObject is present. Defining the 'Orbio' entity and its 'AI HR' services via JSON-LD is critical for LLM entity linking.
- Establish Authoritative Bylines (Authority & Trust): Create dedicated author pages for leadership (e.g., Nacho Travesí mentioned in video metadata) with Person schema and links to LinkedIn/professional bios to satisfy E-E-A-T.
- Add Visible Freshness Signals (Content Structure): Add a visible 'Last Updated' date or a changelog section. While the site was published recently (March 2024), LLMs prioritize content with explicit freshness signals.
- Define Key Technical Entities (Entity Definition): Expand the 'About Us' (Manifiesto) content to include a clear 'Glossary' or 'Definitions' section for technical terms like 'AI Recruitment Agent' and 'Retention Insights'.
- Link Claims to Primary Sources (Citation & Source Quality): Support the 'Results' section (e.g., -81% labor cost) with links to case studies or whitepapers to provide primary source verification for LLMs.