manzas.io — AI Search Visibility Report
Overall score: 70/100
AI search visibility analysis for manzas.io. LLMao scored manzas.io 70/100 across 8 LLM-readiness categories including crawlability, semantic content, structured data, authority signals, and answer-engine clarity.
Analyzed URL
Category breakdown
- readability: 75/100 — Professional and clear, though some procurement jargon is used without immediate definitions.
- schema_markup: 60/100 — The Schema.org Markup has significantly improved, with the introduction of JSON-LD for Organization, WebSite, and WebPage schemas. The FAQPage schema is also present and well-populated. However, there are still opportunities to enhance schema completeness by populating more properties and to ensure all schemas are valid without errors.
- authority_trust: 65/100 — Strong contact info and privacy pages, but lacks detailed author credentials and verified social proof schema.
- citation_sources: 40/100 — Claims are made regarding security and ROI but lack external authoritative citations or primary data links.
- content_freshness: 90/100 — Excellent recency with dates from late 2025 and early 2026 visible on blog and privacy pages.
- content_structure: 80/100 — Good use of H1-H3 hierarchy and semantic sections, though some pages lack a clear Table of Contents for long-form content.
- entity_definition: 70/100 — Consistent branding and clear 'About' information, but lacks Person schema for authors.
- technical_accessibility: 80/100 — Good meta descriptions and social tags, but no explicit AI crawler directives in the provided data.
Top recommendations
- Add Structured Data (JSON-LD) (Schema Markup): Implement Organization, SoftwareApplication, and FAQPage JSON-LD schema to help LLMs identify the business type and service features.
- Enhance Author E-E-A-T Signals (Authority & Trust): Create dedicated author pages for blog contributors with links to LinkedIn and professional bios to satisfy E-E-A-T requirements.
- Add Authoritative Outbound Links (Citation & Source Quality): Include outbound links to industry standards (e.g., GDPR, ISO 27001) or procurement studies to verify technical and security claims.
- Optimize robots.txt for AI Crawlers (Technical Accessibility): Explicitly allow GPTBot, ClaudeBot, and PerplexityBot in robots.txt to ensure full indexing by LLM crawlers.
- Define Industry Terms Explicitly (Entity Definition): Add a 'Glossary' or 'Definitions' section for procurement terms like RFx, e-Invoicing, and Zero-Trust to anchor entity understanding.