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cortex.io
WINTER 2020

cortex.io

Weak AI visibility with 25 of 48 criteria passing. Biggest gap: llms.txt file.

45/100
1 since v1
F
Citation Avg
Coherence gate active - score capped at 50
Answer Readiness
~40% weight
6/10
Content Structure
~25% weight
5/10
Trust & Authority
~15% weight
3/10
Technical Foundation
~10% weight
5/10
AI Discovery
~10% weight
4/10

Verdict

Critical AEO gaps at 45/100 - cortex.io is largely invisible to AI engines. Key strengths include Fact & Data Density, Canonical URL Strategy, and Citation-Ready Writing Quality. Priority gaps: llms.txt File, Schema.org Structured Data, and Comprehensive FAQ Section. Topic coherence is 3/10, which caps the overall score at 50. Focusing content on core expertise areas is the single highest-impact improvement.

#8019of 13363
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How to Improve

Current
45/100
Projected
82/100
39Total Fixes
10Quick Wins
~72hEst. Effort
Quick Wins
Create /llms.txt fileConfigure robots.txt for AI crawlersAdd structured tables and listsAdd direct answer paragraphsAdd ai.txt and content licensingEnhance author and expert schemaImprove query-answer alignmentAdd visible date signalsPackage evidence for AI enginesReduce document weight
Create /llms.txt file
critical|low
Add llms-full.txt with extended content
medium|low
Reduce document weight
high|low
Configure robots.txt for AI crawlers
high|trivial
Improve server response efficiency
critical|medium
Add internationalization signals
critical|medium
Fix HTML structure and meta tags
low|low
Reduce render-blocking resources
low|low
Create complete sitemap.xml
low|low

Top Opportunities10

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.

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.

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.

Write 20-25 word self-contained answer sentences immediately after each H2 heading. 72.4% of AI-cited posts use this pattern - it gives engines a ready-made snippet to quote.

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.

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

Include dateModified schema, visible last-updated dates, and time elements on content pages. Fresh content signals help AI engines prioritize your pages over stale alternatives.

Add more proper nouns throughout content - named sources, organizations, tools, studies, and locations. Cited text averages 20.6% proper nouns; most sites fall well below 15%.

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.

Implement JSON-LD structured data (Organization, Service, Product, FAQPage) on key pages. Schema markup helps AI engines extract and cite your content accurately.

Fix It With AI44

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Site Pages

www.cortex.io/report/the-platform-engineers-guide-to-buil...F32
The Platform Engineer's Guide to Building Platform like a Product | Cortex
www.cortex.io/products/cortex-idpF31
Cortex: IDP to EngOps Platform | Cortex
www.cortex.io/solutions/backstage-migration-helperF28
Backstage Migration Helper | Cortex
www.cortex.io/case-studiesF26
Customers | Cortex
www.cortex.io/products/cortex-mcpF26
MCP | Cortex
www.cortex.io/solutions/self-serviceF30
Self-Service | Cortex
www.cortex.io/products/ai-impactF27
AI Impact | Cortex
www.cortex.io/overviewF27
Cortex | EngOps Platform
www.cortex.io/blogF30
Blog: Engineering Operations Insights | Cortex
www.cortex.io/idpcon/from-deming-to-devopsF31
From Deming to DevOps - John Willis | Cortex
www.cortex.io/idpcon/engineering-paved-paths-for-a-user-f...F31
Blueprints of Innovation: Engineering Paved Paths for a User-friendly Developer Platform | Cortex
Changes since v1Last audited 52 days ago
44
45
+1
View full comparison →
Focus Content on Core TopicsBuild Comprehensive FAQ SectionAdd Owned Data SignalsAdd Answer Capsule PatternsAdd Structured Tables & ListsImprove Question-Answer AlignmentAdd Content Freshness SignalsIncrease Entity DensityIncrease Content DepthAdd Schema.org Structured Data

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