d2l.ai 59 D
🛡️ SEO 31 🤖 GEO 77 ⚡ Perf 62 🏗️ Arch 54

d2l.ai — Global SEODiff Score 59/100

d2l.ai
📊

d2l.ai achieves a 73/100 on the AI-Crawler Reality Index, reflecting above-average readiness for AI-driven discovery. Compared to other education sites (avg score: 57), d2l.ai performs above the benchmark, suggesting strong competitive positioning in AI search. Its server-rendered architecture ensures AI crawlers receive complete HTML on first request, a key advantage for extractability. With a 4.4× bloat ratio, the page delivers its content without excessive boilerplate, giving AI systems a clean extraction path. No structured data was detected, which means AI systems must infer all entities and relationships from raw HTML alone. The site maintains an open-door policy for AI crawlers — GPTBot, ClaudeBot, and other major agents are all allowed.

59
D — Global SEODiff Score
Comprehensive search visibility assessment
Below average — Traditional SEO (31) has the most room for improvement.
🎯 Top Fix: Add Organization + WebSite JSON-LD → +5–8 pts
🔬 Automated SEODiff Assessment · Snapshot: Mar 21, 2026 · 📋 API
Does your site score higher than d2l.ai?
Run the same 40-signal audit on your own domain — free, instant results.
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🧮 Score Transparency — How is this calculated?
🛡️ Traditional SEO (25% weight)31 × 0.25 = 7.8
🤖 AI Readiness / GEO (40% weight)77 × 0.40 = 30.8
⚡ Performance (20% weight)62 × 0.20 = 12.4
🏗️ Architecture & Trust (15% weight)54 × 0.15 = 8.1
Weighted sum = 7.8 + 30.8 + 12.4 + 8.1
Global SEODiff Score = 59 (D)
📊 ACRI Sub-Scores (AI Readiness Detail)
100
Bot Access
avg 92
99
Rendering
avg 93
67
Structure
avg 35
0
Schema
avg 9
50
Tech Stack
avg 63
🔀
Visibility Delta: Google vs AI
Google (Tranco)
Top 8%
Rank #81509
+17 pts
Gap
AI (ACRI)
Top 25%
Score 73/100

d2l.ai punches above its weight in AI — AI visibility exceeds Google ranking. This is a competitive moat worth protecting. ACRI measures technical crawler readiness. Read the methodology →

Why d2l.ai ranks here

Tech stackCustom / Proprietary
Industryeducation
RenderingSSR
Schema coverage0 blocks
Token bloat4.4×

Fastest improvements

  • Add basic Organization and WebSite JSON-LD to fix “0 schema blocks” (see Schema Coverage).
  • Reduce token bloat (navigation/footer/code) so agents reach your main content faster (see Token Bloat).
  • Create an llms.txt file so AI crawlers can discover your content structure without heavy crawling. Generate llms.txt →
  • Run a full entropy audit to find which DOM regions waste the most tokens. Run Entropy Audit →
🧪

JavaScript Rendering Check

We check what AI crawlers miss when they skip JavaScript execution.

Running headless browser to simulate AI extraction…
🛡️

Traditional SEO

31/100 25 % of Global Score 🟡 Medium Confidence

📝 Title Tag

71 chars
Too long

Optimal range: 30–60 characters for SERP display.

📋 Meta Description

0 chars
Missing

Optimal range: 120–160 characters for snippet control.

🔤 Heading Hierarchy

  • ✓ Exactly 1 <h1> tag — found 1
  • ✓ Has <h2> headings — found 9
  • ✓ <h2> not before <h1>

🔍 Indexability

  • ✗ Canonical tag present
  • ✓ No noindex directive
  • ✓ Meta viewport set
  • ✓ HTML lang attribute → en
  • ➖ Hreflang tags — N/A (single language site)
  • ✓ Googlebot allowed by robots.txt

🌐 Social / OpenGraph

  • ✗ og:title
  • ✗ og:description
  • ✗ og:image
  • ✗ twitter:card
📐 How the SEO Pillar score is calculated

SEO Pillar = Title (20 pts) + Meta Desc (20 pts) + Heading Hierarchy (20 pts) + Indexability (20 pts) + Social/OG (20 pts)

Each sub-score is derived from the checks above. Canonical tag, lang attribute, og:image, and a single H1 are the highest-impact items.

🤖

AI Readiness / GEO

77/100 40 % of Global Score 🟢 High Confidence

This pillar aggregates citation share, hallucination risk, bot access, schema health, and content extractability. The individual diagnostic sections below contribute to this score.

🔗

Citation Alternatives

Research
💡
Insight: In the education sector, educationdirectory.com.au (ACRI: 86) currently has stronger AI extractability. AI models tend to prefer sources with higher semantic structure and schema coverage. Domains with ACRI < 40 see 3.5× more hallucinations. Read the research →
d2l.ai
60
Your ACRI Score
86
Industry Peer ACRI
AI models prioritize pages with strong semantic structure and schema coverage. educationdirectory.com.au has schema coverage of 4 blocks and uses Custom / Proprietary. Improve your score by implementing the remediation patches below.
📊 Side-by-Side Comparison →
🚨

Hallucination Risk

Research

Is AI lying about your brand? This panel measures how likely LLMs are to hallucinate facts when extracting information from your page.

Analyzing hallucination risk…

🤖 Bot Access Matrix

GPTBot (OpenAI)
Allowed
ClaudeBot (Anthropic)
Allowed
CCBot (Common Crawl)
Allowed
Google-Extended
Allowed
Googlebot
Allowed

👻 Rendering (Ghost Ratio) Docs

Ghost Ratio 5%
0% — Safe 50% 100% — Risk
Status Server-Side Rendered (Safe)
Rendering Type SSR

📊 Structure & Information Density Docs

Structure Grade 67/100 — Good
Structured Elements 588 elements (588 lists, 0 rows, 0 headers)
Total Words4419
Raw Density13.3%

🏷️ Schema Health Docs

Organization Schema ❌ Missing
Product / Service Schema ⚠️ Not Found
Total Schema Blocks0 — No JSON-LD detected

Schema Coverage Map

0/7 schema types detected
❌ Organization
❌ Product/Service
❌ Breadcrumb
❌ FAQ
❌ Article
❌ WebSite
💡Organization schema missing. AI models cannot identify your brand entity. Without it, your brand won't appear in Knowledge Panels or be associated with your content.
💡Product / Service schema missing. AI models don't know this is a SaaS product. Add Product or SoftwareApplication schema so AI understands what you offer and can surface pricing/features.
💡BreadcrumbList schema missing. AI cannot understand your site hierarchy or how pages relate to each other.
💡FAQ schema missing. Adding FAQPage schema lets AI models directly extract Q&A pairs for Featured Snippets and chatbot answers.
💡WebSite schema missing. Add WebSite + SearchAction so Google can generate a Sitelinks Search Box for your brand in AI results.

📐 AI Efficiency Metrics Docs

65
AI Extractability
Low
Crawl Cost
None
Blocklist Risk
Extractability65/100 — AI models can partially extract answers from this page
Crawl CostLow (30/100) — efficient for AI crawlers to process
Blocklist RiskNone — 0 of 5 AI crawlers blocked

Token Bloat Research

22%
🗑️ 78%
Useful Content (41.8 KB)Bloat (142.2 KB)
Token Bloat Ratio4.4× — Lean

Multimodal Readiness

Visual Context5% Optimized for Vision
Image Alt Coverage2 / 37 images have alt text

TDM Rights

TDM-Reservation HeaderNot set
X-Robots-Tag: noaiNot set
💡Only 5% of images have alt text. Add descriptive alt attributes so multimodal AI (ChatGPT Vision) can understand your images.

🔥 Structural Entropy Check Research

15 Entropy
Poor Token Bloat: High
Noise Ratio: 77.3% · SNR: 0.29 · Signal: 10703 / Noise: 36415 tokens

🔬 AI-Crawler Simulation

See your website the way AI crawlers do. CSS stripped, structure labeled, content chunked.

🌐
This is what humans see — styled, branded, visual.
Toggle to "AI Agent View" to see what GPTBot, ClaudeBot, and other AI crawlers actually extract from this page.
🤖

AI Answer Preview

NEW

See how AI models summarize your site. Left: your actual content. Right: what the LLM extracts and says about you.

Simulating AI extraction…
🧠

The LLM Interpretation

AI-VERIFIED

SEODiff AI analyzed the extracted content of d2l.ai and produced this structured business intelligence. Fields marked SEMANTIC VOID indicate information the AI could not find — a critical gap in your site’s machine-readability.

Core Offering
Dive into Deep Learning is an interactive, open-source deep learning textbook and reference, designed to help users learn and implement
Target Audience
Students, researchers, data scientists, and anyone seeking to learn or deepen their understanding of deep learning.
Pricing Model
Free to use with options for paid resources and support (e.g., SageMaker Studio Lab).
🔗 Integration Partners
PyTorchNumPyMXNetJAXTensorFlowSageMaker Studio Lab
🏆 Competitive Moat
Comprehensive, interactive learning experience with a strong community, combining theory, code, and practical exercises across various deep learning topics.
📊 Content Depth
9/10
🔄 Programmatic SEO Signals
Integration directory pagesTemplate comparison pages
⚡ Key Pain Points
• Lack of structured FAQ schema
• Thin landing pages for features
Analyzed by SEODiff AI · 2026-03-04

🔧 Tech Stack

AI-Readiness Score50/100
ServerAmazonS3
CDN
HTTP Status200
Load Time498 ms
Raw HTML Size184.1 KB
Visible Text Size41.8 KB

Performance & Speed

62/100 20 % of Global Score 🟢 High Confidence

⏱️ Time to First Byte

498 ms
Acceptable — room for improvement

Google considers <200 ms "good". AI crawlers may have even shorter timeouts.

📦 Page Weight

2032
DOM nodes
184 KB
HTML payload
Moderate weight — acceptable for most scenarios

🗄️ Cache & CDN

  • ✗ Cache-Control header
  • ✗ CDN cache status
  • ✗ CDN detected

🔬 Tracker Tax

0
tracker scripts
0
third-party domains
0.0%
token overhead
Minimal tracker load — clean signal for bots
📐 How the Performance Pillar score is calculated

Perf Pillar = TTFB (35 pts) + Page Weight (25 pts) + Cache/CDN (20 pts) + Tracker Tax (20 pts)

TTFB <200 ms = full marks. DOM >3000 or payload >300 KB incurs heavy penalties. Tracker scripts beyond 5 reduce score.

🏗️

Architecture & Trust

54/100 15 % of Global Score 🟡 Medium Confidence

🗺️ Sitemap & Robots

  • ✗ Sitemap declared in robots.txt
  • ✓ Googlebot allowed
  • ✓ GPTBot allowed
  • ✓ ClaudeBot allowed

🔗 Linking

624
internal links
28
external links
Good internal linking — helps crawlers discover content

🔒 Security & Trust

  • ✗ HSTS header (Strict-Transport-Security)
  • ✗ Content-Security-Policy header
  • ✓ HTTP status 200 OK (got 200)

♿ Accessibility Signals

  • ✓ HTML lang attribute → en
  • ✓ Meta viewport for mobile
  • ✓ Single H1 for screen readers
📐 How the Architecture Pillar score is calculated

Arch Pillar = Sitemap & Robots (30 pts) + Linking (25 pts) + Security (25 pts) + Accessibility (20 pts)

Having a valid sitemap, allowing AI bots, HSTS, and a good internal link count are the highest-impact items.

🏅 AI-Verified Trust Badge

Your site scores 60/100. Reach 80+ to unlock the green "AI-Verified" badge. Fix the issues below to improve your score.

AI-Verified badge for d2l.ai
Pending Audit — score below 80 threshold
<a href="https://seodiff.io/radar/domains/d2l.ai" rel="noopener"><img src="https://seodiff.io/api/v1/badge?domain=d2l.ai" alt="AI-Verified by SEODiff" width="280" height="52"></a>

💡 Paste in your site footer, GitHub README, or email signature. Badge updates automatically as your score changes.

� Deep Crawl Analysis 21 pages · Deep-10

Homepage ACRI
60
Single-page score
+7
Consistent readability
Δ delta
Site-Wide ACRI
67
Avg across 21 pages · Range 67–67
Total Words
58485
Avg Bloat
13.5×
Page Type ACRI Token Bloat Words Status
https://d2l.ai/pricing
Dive into Deep Learning — Dive into Deep Learning 1.0.3 documentation
pricing 67 13.5× 2785
https://d2l.ai/api
Dive into Deep Learning — Dive into Deep Learning 1.0.3 documentation
docs 67 13.5× 2785
https://d2l.ai/guides
Dive into Deep Learning — Dive into Deep Learning 1.0.3 documentation
blog 67 13.5× 2785
https://d2l.ai/resources
Dive into Deep Learning — Dive into Deep Learning 1.0.3 documentation
blog 67 13.5× 2785
https://d2l.ai/about
Dive into Deep Learning — Dive into Deep Learning 1.0.3 documentation
about 67 13.5× 2785
https://d2l.ai/help
Dive into Deep Learning — Dive into Deep Learning 1.0.3 documentation
support 67 13.5× 2785
https://d2l.ai/features
Dive into Deep Learning — Dive into Deep Learning 1.0.3 documentation
product 67 13.5× 2785
https://d2l.ai/products
Dive into Deep Learning — Dive into Deep Learning 1.0.3 documentation
product 67 13.5× 2785
https://d2l.ai/solutions
Dive into Deep Learning — Dive into Deep Learning 1.0.3 documentation
product 67 13.5× 2785
https://d2l.ai/blog
Dive into Deep Learning — Dive into Deep Learning 1.0.3 documentation
blog 67 13.5× 2785
https://d2l.ai/docs
Dive into Deep Learning — Dive into Deep Learning 1.0.3 documentation
docs 67 13.5× 2785
https://d2l.ai/demo
Dive into Deep Learning — Dive into Deep Learning 1.0.3 documentation
conversion 67 13.5× 2785
https://d2l.ai/get-started
Dive into Deep Learning — Dive into Deep Learning 1.0.3 documentation
conversion 67 13.5× 2785
https://d2l.ai/case-studies
Dive into Deep Learning — Dive into Deep Learning 1.0.3 documentation
social-proof 67 13.5× 2785
https://d2l.ai/faq
Dive into Deep Learning — Dive into Deep Learning 1.0.3 documentation
support 67 13.5× 2785
https://d2l.ai/contact
Dive into Deep Learning — Dive into Deep Learning 1.0.3 documentation
support 67 13.5× 2785
https://d2l.ai/support
Dive into Deep Learning — Dive into Deep Learning 1.0.3 documentation
support 67 13.5× 2785
https://d2l.ai/integrations
Dive into Deep Learning — Dive into Deep Learning 1.0.3 documentation
integrations 67 13.5× 2785
https://d2l.ai/security
Dive into Deep Learning — Dive into Deep Learning 1.0.3 documentation
trust 67 13.5× 2785
https://d2l.ai/trust
Dive into Deep Learning — Dive into Deep Learning 1.0.3 documentation
trust 67 13.5× 2785
Showing 20 of 21 pages. Unlock full subpage table →
📂
Health by Sub-Directory
Average ACRI and top issues aggregated by URL path prefix
Path Pages Avg ACRI Ghost % Bloat Top Issue
/pricing/ 1 67 0% 13.5× High JS Bloat
/products/ 1 67 0% 13.5× High JS Bloat
/api/ 1 67 0% 13.5× High JS Bloat
/get-started/ 1 67 0% 13.5× High JS Bloat
/features/ 1 67 0% 13.5× High JS Bloat
/docs/ 1 67 0% 13.5× High JS Bloat
/contact/ 1 67 0% 13.5× High JS Bloat
/faq/ 1 67 0% 13.5× High JS Bloat
/guides/ 1 67 0% 13.5× High JS Bloat
/integrations/ 1 67 0% 13.5× High JS Bloat
/case-studies/ 1 67 0% 13.5× High JS Bloat
/blog/ 1 67 0% 13.5× High JS Bloat
/security/ 1 67 0% 13.5× High JS Bloat
/help/ 1 67 0% 13.5× High JS Bloat
/demo/ 1 67 0% 13.5× High JS Bloat
🔗
Outbound External Citations
0 unique external domains cited across 21 pages
pratikac.github.io ×21
aaronkl.github.io ×21
github.com ×21
courses.d2l.ai ×21
d2l.aivivn.com ×21
preview.d2l.ai ×21
cs.cmu.edu ×21
cims.nyu.edu ×21
🔄 Re-Crawl & Update 📡 Track this Domain

Scores update automatically each month. Create a free account for on-demand re-crawls (3/month free).

🔌 API Access

Pull this data programmatically. All sub-page metrics are available via our public API.

curl https://seodiff.io/api/v1/deep10/domain/d2l.ai

Get your free API key — 100 requests/month included.

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📊 Semantic Share of Voice

How often would an AI cite d2l.ai when users ask about topics in this domain's niche? We run entity queries through our 188k-page search index and measure citation probability.

Analyzing citation landscape…

🩹

Remediation Patches

COPY-PASTE

Auto-generated code fixes tailored to d2l.ai. Copy and paste these into your codebase to improve AI visibility. These patches are mathematically proven to increase extraction accuracy →

Add Organization JSON-LD
High Impact ⏱ 5 min
AI models cannot identify your brand entity without Organization schema. This is the #1 fix for AI visibility.
html
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "D2l",
  "url": "https://d2l.ai",
  "logo": "_static/favicon.png",
  "sameAs": []
}
</script>
Add WebSite + SearchAction JSON-LD
High Impact ⏱ 5 min
Enables the Sitelinks Search Box in Google and allows AI to understand your site structure.
html
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "WebSite",
  "name": "D2l",
  "url": "https://d2l.ai",
  "potentialAction": {
    "@type": "SearchAction",
    "target": "https://d2l.ai/search?q={search_term_string}",
    "query-input": "required name=search_term_string"
  }
}
</script>
Add FAQ Schema
Medium Impact ⏱ 10 min
FAQ schema lets AI models directly extract Q&A pairs. This is the easiest way to get featured in AI responses.
html
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "What is D2l?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Add your answer here — describe what D2l does in 1-2 sentences."
      }
    },
    {
      "@type": "Question",
      "name": "How does D2l work?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Explain the key features and how users interact with D2l."
      }
    }
  ]
}
</script>
📈

Projected Impact

ROI EST.

If you apply the patches above, here's the estimated improvement for d2l.ai:

Current Score
73
Projected Score
89
Improvement
+16 pts
Add Organization schema +6 pts
Add WebSite schema +4 pts
Reduce token bloat +3 pts
Add FAQ schema +3 pts

*Estimates based on SEODiff's scoring model. Actual results depend on implementation quality.

📋 Data Export

Download scores and metadata for audits, client reports, or CI/CD pipelines. Exports contain computed metrics only (no copyrighted content).

All data is generated automatically and updated with each crawl. JSON exports contain scores and metadata only (no copyrighted content).

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🧭 Self-Diffing (Private Layer)

For owned domains, combine this world snapshot with private drift + regression history.
Template Drift
Track in My Site
Drift → Traffic Impact
In development coming soon
Regression Incidents
Track in My Site
Internal Linking
Deep Audit graph
Semantic Structure
GEO view in Deep Audit
Content Quality
Thin/duplicate tracking

🕒 History

Score over timeAvailable in My Site history
Drift eventsTemplate timeline + incidents
Drift → Revenue AttributionComing soon
Schema/rendering/extractability changesTracked per scan in project history
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