ave.ai — AI Search Visibility Report
Overall score: 42/100
AI search visibility analysis for ave.ai. LLMao scored ave.ai 42/100 across 8 LLM-readiness categories including crawlability, semantic content, structured data, authority signals, and answer-engine clarity.
Analyzed URL
Category breakdown
- readability: 50/100 — The page is mostly numbers and tickers; very little prose to evaluate for clarity or flow.
- schema_markup: 0/100 — No JSON-LD blocks found in the provided HTML. Relies entirely on meta tags.
- authority_trust: 25/100 — Lacks visible contact info, trust pages, and author credentials. Social proof is implied by user count but not structured.
- citation_sources: 30/100 — While it links to various blockchains, it lacks outbound links to authoritative news or primary documentation.
- content_freshness: 40/100 — Real-time data is present, but there are no explicit publication or modification dates in the metadata.
- content_structure: 20/100 — The page is almost entirely a data table with no H1-H3 hierarchy or semantic sectioning.
- entity_definition: 35/100 — No About page or author identification. Brand consistency is the only saving grace.
- technical_accessibility: 65/100 — Good meta descriptions and social meta, but heavily dependent on JS for the main data table.
Top recommendations
- Add Core JSON-LD Schema (Schema.org Markup): Implement Organization, WebSite, and SoftwareApplication JSON-LD schema to define the entity for LLMs.
- Establish Entity Authority (Authority & Trust Signals): Create a dedicated 'About Us' page with team information, physical address, and editorial standards to improve E-E-A-T.
- Improve Semantic Hierarchy (Content Structure): Replace the current image-heavy layout with semantic HTML (H1, H2 tags) to describe the platform's features.
- Implement Freshness Signals (Content Freshness): Add visible 'Last Updated' timestamps to the data tables or a blog section to signal content recency to crawlers.
- Reduce JS Dependency for Content (Technical Accessibility): Ensure core platform descriptions are accessible in the HTML source without requiring JavaScript execution.