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tint.ai

tint.ai

Weak AI visibility with 23 of 48 criteria passing. Biggest gap: llms.txt file.

Developer Tools & InfrastructureDeveloper Platforms
44/100
1 since v1
F
Citation Avg
Coherence gate active - score capped at 60
Answer Readiness
~40% weight
5/10
Content Structure
~25% weight
4/10
Trust & Authority
~15% weight
3/10
Technical Foundation
~10% weight
5/10
AI Discovery
~10% weight
3/10

Verdict

Critical AEO gaps at 44/100 - tint.ai is largely invisible to AI engines. Key strengths include Canonical URL Strategy, Duplicate Content Blocks, and Entity Density. Priority gaps: llms.txt File, Schema.org Structured Data, and Comprehensive FAQ Section. Topic coherence is moderate at 5/10, capping the score at 60. Tighter topical focus would lift this ceiling.

How to Improve

Current
44/100
Projected
78/100
43Total Fixes
12Quick Wins
~98hEst. Effort
Quick Wins
Create /llms.txt fileAdd question-based headingsStrengthen entity authority (NAP)Configure robots.txt for AI crawlersAdd direct answer paragraphsAdd ai.txt and content licensingAdd visible date signalsFocus blog content on core expertiseAdd first-hand experience signalsMake content creators clearly visibleImprove citation-ready writing qualityEliminate cross-page duplicate content
Create /llms.txt file
critical|low
Add llms-full.txt with extended content
medium|low
Create complete sitemap.xml
critical|medium
Configure robots.txt for AI crawlers
critical|low
Add internationalization signals
critical|medium
Fix HTML structure and meta tags
low|low
Improve server response efficiency
medium|low
Reduce document weight
low|low
Reduce render-blocking resources
low|low

Top Opportunities10

Expand articles to 1000+ words with structured H2/H3 sections, comparison tables, and expert analysis. Thin content (under 300 words) is rarely cited by AI engines. Deep, well-structured articles demonstrate expertise.

Add specific numbers, percentages, statistics, and data points throughout your content. Fact-dense content gives AI engines concrete data to cite rather than vague claims.

Ensure blog content consistently covers your core expertise areas rather than scattering across unrelated topics. AI engines build authority models - a site about "Medicare coverage" that also publishes about humidifiers and groceries dilutes its topical authority.

Publish original research, statistics, case studies, or proprietary data that AI engines can cite. Unique data points make your content a primary source rather than a derivative one.

Ensure every question-format heading (H2/H3) is followed by a direct answer paragraph. This pattern is ideal for AI engine snippet extraction.

Use HTML tables for comparison data and ordered/unordered lists for features, steps, and specifications. Structured data formats are directly extractable by AI engines for answers.

Create a dedicated FAQ page with FAQPage schema markup. Cover common questions about your products, services, and industry to become a direct answer source for AI engines.

Write concise, standalone answer paragraphs (2-3 sentences) immediately after question headings. These "snippet-ready" paragraphs are ideal for AI engine citations.

Include "our analysis", "our data", "our testing" phrases backed by original research or proprietary data. 52.2% of AI-cited posts contain owned data signals.

Define the primary entity in the first 500 characters, use consistent terminology (same term 70%+), and add "unlike X" signals to help AI engines distinguish your topics.

Fix It With AI44

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Site Pages

www.tint.aiF39
Tint — Embedded Insurance Platform & MGA
Changes since v1Last audited 52 days ago
45
44
-1
View full comparison →
Increase Content DepthIncrease Fact & Data DensityFocus Content on Core TopicsAdd Original Data & Case StudiesImprove Question-Answer AlignmentAdd Structured Tables & ListsBuild Comprehensive FAQ SectionAdd Direct Answer ParagraphsAdd Owned Data SignalsAdd Entity Disambiguation

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