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hashgraph.com

hashgraph.com

Moderate AI visibility with 30 of 48 criteria passing. Biggest gap: llms.txt file.

Developer Tools & InfrastructureSecurity & Compliance
51/100
2 since v1
D
Citation Avg
Coherence gate active - score capped at 55
Answer Readiness
~40% weight
6/10
Content Structure
~25% weight
5/10
Trust & Authority
~15% weight
5/10
Technical Foundation
~10% weight
5/10
AI Discovery
~10% weight
6/10

Verdict

Below-average AEO readiness at 51/100 - multiple areas need attention. Key strengths include RSS/Atom Feed, Canonical URL Strategy, and Answer-First Placement. Priority gaps: llms.txt File, Comprehensive FAQ Section, and Speakable Schema. Topic coherence is 4/10, which caps the overall score at 55. Focusing content on core expertise areas is the single highest-impact improvement.

How to Improve

Current
51/100
Projected
80/100
41Total Fixes
11Quick Wins
~78hEst. Effort
Quick Wins
Create /llms.txt fileConfigure robots.txt for AI crawlersLink orphan pages into site navigationImplement semantic HTML5 elementsAdd definition-style contentAdd ai.txt and content licensingEnhance author and expert schemaFocus blog content on core expertiseImprove citation-ready writing qualityPackage evidence for AI enginesReduce render-blocking resources
Create /llms.txt file
critical|low
Add llms-full.txt with extended content
medium|low
Configure robots.txt for AI crawlers
high|trivial
Reduce render-blocking resources
high|low
Fix HTML structure and meta tags
low|low
Add internationalization signals
critical|medium
Reduce document weight
medium|low
Improve server response efficiency
medium|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.

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.

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.

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.

Write self-contained definition sentences and single-claim statements that AI engines can quote directly. Avoid pronouns like "this" or "that" at the start of answer paragraphs.

Show direct use, testing, implementation, or lived experience with concrete observations, examples, screenshots, and lessons learned.

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

www.hashgraph.com/wp-content/uploads/2025/11/Docs.zipF27
www.hashgraph.com/case-study/the-institutes-riskstream-co...F39
The Institutes RiskStream Collaborative | Hashgraph
www.hashgraph.com/blogF38
Blog | Hashgraph
Changes since v1Last audited 52 days ago
53
51
-2
View full comparison →
Focus Content on Core TopicsImprove Question-Answer AlignmentAdd Structured Tables & ListsIncrease Content DepthBuild Comprehensive FAQ SectionAdd Owned Data SignalsAdd Answer Capsule PatternsImprove Citation-Ready WritingAdd First-Hand Experience SignalsPackage Evidence for AI

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