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boundaryml.com
WINTER 2023

boundaryml.com

Moderate AI visibility with 27 of 48 criteria passing. Biggest gap: llms.txt file.

Developer Tools & InfrastructureDeveloper Platforms
57/100
2 since v1
F
Citation Avg
Answer Readiness
~40% weight
8/10
Content Structure
~25% weight
6/10
Trust & Authority
~15% weight
3/10
Technical Foundation
~10% weight
6/10
AI Discovery
~10% weight
5/10

Verdict

Below-average AEO readiness at 57/100 - multiple areas need attention. Key strengths include Original Data & Expert Analysis, Sitemap Completeness, and Table & List Extractability. Priority gaps: llms.txt File, Schema.org Structured Data, and Comprehensive FAQ Section.

How to Improve

Current
57/100
Projected
83/100
36Total Fixes
8Quick Wins
~68hEst. Effort
Quick Wins
Create /llms.txt fileAdd question-based headingsConfigure robots.txt for AI crawlersLink orphan pages into site navigationAdd ai.txt and content licensingImprove query-answer alignmentPackage evidence for AI enginesClarify entity boundaries
Create /llms.txt file
critical|low
Add llms-full.txt with extended content
medium|low
Fix HTML structure and meta tags
medium|low
Configure robots.txt for AI crawlers
high|trivial
Add internationalization signals
critical|medium
Reduce document weight
medium|low
Improve server response efficiency
medium|low
Reduce render-blocking resources
medium|low

Top Opportunities10

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.

Add question-based headings (H2/H3) throughout your content. Use "What is...", "How does...", "Why should..." patterns that match how users query AI assistants.

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

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.

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.

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.

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

Add Organization schema with consistent name, address, phone (NAP). Include sameAs links to social profiles and authoritative directories to strengthen entity recognition.

Add inline citations to external sources, "According to [Source]..." attribution phrases, and a Sources section at the end of key articles.

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Site Pages

boundaryml.com/twitter-imageF29
boundaryml.com/blogF37
BAML Blog - Insights, Tutorials, and AI Development Updates
boundaryml.com/learn/everythingF36
BAML
boundaryml.com/why-the-f-did-we-make-a-languageD42
BAML
Changes since v1Last audited 76 days ago
59
57
-2
View full comparison →
Build Comprehensive FAQ SectionAdd Owned Data SignalsRestructure Content as Q&AImprove Question-Answer AlignmentIncrease Content DepthAdd Entity DisambiguationAdd Answer Capsule PatternsAdd Schema.org Structured DataStrengthen Entity Authority (NAP)Package Evidence for AI

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