manzas.io — AI Search Visibility Report
Overall score: 56/100
AI search visibility analysis for manzas.io. LLMao scored manzas.io 56/100 across 8 LLM-readiness categories including crawlability, semantic content, structured data, authority signals, and answer-engine clarity.
Analyzed URL
Category breakdown
- readability: 90/100 — Excellent readability with clear, active voice and well-handled technical jargon related to procurement.
- schema_markup: 0/100 — No JSON-LD schema was detected in the provided HTML, which is a significant missed opportunity for LLM optimization. All tests received a score of 0/20.
- authority_trust: 55/100 — Basic trust signals like contact email and privacy pages are present, but lack of author credentials and detailed company history limits trust.
- citation_sources: 40/100 — The site makes several claims about efficiency and security but lacks external citations or primary source data to verify them.
- content_freshness: 75/100 — The site is current for 2026, with a 2026 copyright and recent pilot program mentions, though specific 'last updated' dates are missing.
- content_structure: 70/100 — Good use of semantic HTML and sections, but the heading hierarchy is inconsistent (skipping H2s in some sections).
- entity_definition: 60/100 — The brand name is consistent, but the lack of an About page and Organization schema makes it harder for LLMs to define the entity.
- technical_accessibility: 80/100 — Strong meta descriptions and social meta tags are present, though AI-specific crawler instructions are missing.
Top recommendations
- Add JSON-LD Structured Data (Schema Markup): Implement JSON-LD schema for Organization, WebSite, and FAQPage. Currently, no structured data was found in the HTML, which prevents LLMs from definitively identifying the entity and its services.
- Enhance Authoritative Signals (E-E-A-T) (Authority & Trust): Create a dedicated 'About Us' page and include detailed author bios for blog content. LLMs prioritize content with clear expertise and human accountability (E-E-A-T).
- Optimize Heading Hierarchy (Content Structure): Fix the heading hierarchy on the homepage. The current structure skips levels (H1 to H3) and uses H3 tags for minor UI elements, which confuses LLM parsers.
- Add Authoritative Outbound Citations (Citation & Source Quality): Include outbound links to authoritative industry reports or data privacy standards (like GDPR/BSI) to back up security and efficiency claims.
- Explicitly Allow AI Crawlers (Technical Accessibility): Create a robots.txt file that explicitly allows AI crawlers like GPTBot, ClaudeBot, and PerplexityBot to ensure full indexing by LLM-based search engines.