Vector Readiness Assessment
Evaluate your content's readiness for dense retrieval systems and get passage-level optimization recommendations for AI search success.
What We Assess
Our comprehensive analysis evaluates your content across the key factors that determine success in AI-powered search systems.
Vector Similarity
Measure semantic alignment between your content and target queries using cosine similarity calculations.
Semantic Completeness
Evaluate whether your passages provide complete, self-contained answers without requiring additional context.
Entity Density
Analyze Knowledge Graph entity alignment and relationship mapping for improved fan-out compatibility.
Citation Worthiness
Assess factual accuracy, authority signals, and content structure for AI citation likelihood.
Assessment Scoring
Your content receives a comprehensive score across four key dimensions, with specific recommendations for improvement in each area. Our scoring is based on analysis of 10,000+ AI Overview results.
Start Your Assessment
Enter your content and target query to receive a comprehensive vector readiness analysis.
Our Assessment Methodology
Based on extensive research and analysis of AI search ranking factors, our assessment provides actionable insights for optimization.
Vector Similarity Analysis
What We Measure
- • Cosine similarity between content and query embeddings
- • Semantic density and concept coverage
- • Keyword-concept alignment strength
Optimization Recommendations
- • Specific word choice improvements
- • Concept density optimization
- • Semantic gap identification
Semantic Completeness Evaluation
Self-Containment
Can the passage answer the query without additional context?
Information Density
Does the content provide sufficient detail and examples?
Clarity & Flow
Is the information presented in a logical, clear manner?
Entity & Citation Analysis
Entity Mapping
We identify and analyze Knowledge Graph entities within your content, measuring their density and relationship strength.
Target: 3-5 entities per 100 words for optimal performance
Citation Worthiness
Assessment of factual accuracy, source attribution, and authority signals that make content suitable for AI citation.
Key factors: Factual claims, data sources, expert attribution
Sample Assessment Report
See what insights you'll receive from your vector readiness assessment.
Overall Vector Readiness Score
Dimension Scores
Priority Improvements
- 1. Increase entity density by 40% (add 2-3 more entities)
- 2. Add authoritative data sources and citations
- 3. Improve semantic completeness with specific examples
Recommended Next Steps
Your content shows strong vector similarity but needs entity enrichment and citation improvements. Focus on adding Knowledge Graph entities and authoritative sources to increase AI citation likelihood by an estimated 34%.
Ready to Optimize Your Content?
Get your free vector readiness assessment and discover exactly how to improve your AI search performance.