vapi.ai — AI Search Visibility Report
Overall score: 68/100
AI search visibility analysis for vapi.ai. LLMao scored vapi.ai 68/100 across 8 LLM-readiness categories including crawlability, semantic content, structured data, authority signals, and answer-engine clarity.
Analyzed URL
Category breakdown
- readability: 85/100 — Highly readable for the target developer audience. Jargon is used appropriately and code examples provide clarity.
- schema_markup: 40/100 — Basic metadata is present, but advanced JSON-LD for the product, organization, or FAQs is missing.
- authority_trust: 60/100 — Strong social proof with enterprise logos and testimonials, but lacks clear author credentials and a dedicated about page.
- citation_sources: 40/100 — Claims are made about performance (sub-500ms) without direct links to benchmarks or primary data sources.
- content_freshness: 50/100 — No visible publication or modification dates on the homepage, though the tech stack (gpt-4o) implies recency.
- content_structure: 90/100 — Excellent use of H1-H3 hierarchy and semantic sections. Code blocks are well-structured for LLM ingestion.
- entity_definition: 60/100 — Brand consistency is high, but the lack of an About page or Person schemas for leadership limits entity clarity.
- technical_accessibility: 80/100 — Good meta descriptions and social tags. Content is largely accessible, though robots.txt was not explicitly verified for AI bots.
Top recommendations
- Add Product and FAQ Schema (Schema Markup): Implement SoftwareApplication and FAQPage schema to help LLMs understand product capabilities and answer common user questions directly.
- Establish Entity Authority (Authority & Trust): Add a dedicated 'About Us' page and link to specific author profiles for blog posts to establish E-E-A-T.
- Improve Citation Quality (Citation & Source Quality): Include external links to documentation for integrated models (OpenAI, Anthropic) and primary data sources for performance claims.
- Signal Content Recency (Content Freshness): Add 'Last Updated' timestamps to the homepage and technical documentation to signal content recency to LLM crawlers.
- Optimize AI Crawler Access (Technical Accessibility): Explicitly allow GPTBot and ClaudeBot in robots.txt to ensure full indexing of technical documentation.