tines.io — AI Search Visibility Report
Overall score: 78/100
AI search visibility analysis for tines.io. LLMao scored tines.io 78/100 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 readability with clear, active voice. Technical jargon is present but usually contextualized by the 'Solutions' sections.
- schema_markup: 40/100 — Minimal JSON-LD found in the provided snippet. Relies heavily on Meta tags which are less effective for LLM entity mapping than structured data.
- authority_trust: 75/100 — Strong social proof with G2/Gartner ratings and enterprise logos, but lacks detailed author credentials and explicit publication history on the homepage.
- citation_sources: 80/100 — Excellent use of primary sources via case studies (Mars, Snowflake, etc.), though outbound links to third-party research are limited on the homepage.
- content_freshness: 95/100 — Very high freshness with specific references to 'March 2026' and 'RSA 2026', indicating active maintenance.
- content_structure: 80/100 — Good use of semantic HTML and clear sections, though heading hierarchy is slightly inconsistent in the navigation/hero transition.
- entity_definition: 85/100 — Brand entity is very strong and consistent. About page is present, but term definitions for 'Intelligent Workflows' could be more structured.
- technical_accessibility: 85/100 — Excellent meta descriptions and social meta tags. Content is largely accessible, though JS dependency for Gatsby-rendered images is noted.
Top recommendations
- Add Structured Data (JSON-LD) (Schema Markup): Implement detailed JSON-LD schema (Organization, SoftwareApplication, and FAQPage) to help LLMs explicitly identify your product features and entity relationships.
- Enhance Author Transparency (Authority & Trust): Add explicit author bylines with links to bio pages or LinkedIn profiles for blog posts to satisfy E-E-A-T requirements for LLMs.
- Fix Heading Hierarchy (Content Structure): Ensure a strict H1-H2-H3 hierarchy. Currently, some sections use H3 tags (e.g., 'Solutions') without preceding H2s in the visual flow.
- Optimize AI Crawler Access (Technical Accessibility): Create a robots.txt file that explicitly allows AI crawlers like GPTBot, ClaudeBot, and PerplexityBot to ensure full indexing of documentation.
- Define Core Technical Entities (Entity Definition): Create a dedicated 'Glossary' or 'Definitions' section for technical terms like 'SOAR', 'No-code automation', and 'Intelligent Workflows' to anchor entity nodes.