together.ai 57 D
🛡️ SEO 58 🤖 GEO 61 ⚡ Perf 41 🏗️ Arch 67

together.ai — Global SEODiff Score 57/100

together.ai
📊

At 76/100, the ACRI for together.ai indicates strong fundamentals in AI extractability, surpassing the majority of indexed sites. Within the developer vertical, this places together.ai above the industry average of 57 —, suggesting strong competitive positioning in AI search. Server-side rendering keeps the ghost ratio near zero, giving AI systems direct access to all visible content. The bloated 33.1× token ratio highlights an urgent need to clean up non-content markup, scripts, and navigation clutter. Minimal structured data (1 block) limits the site's ability to communicate entity relationships to AI systems. Robots.txt grants unrestricted access to the key AI user-agents, which is the strongest starting position for AI visibility.

57
D — Global SEODiff Score
Comprehensive search visibility assessment
Below average — Performance (41) has the most room for improvement.
🎯 Top Fix: Reduce token bloat (33×) → +5–10 pts
🔬 Automated SEODiff Assessment · Snapshot: Mar 20, 2026 · 📋 API
📈 ACRI Trend 19 snapshots
Feb 22 Mar 20
🔔 Recent AI Indexing Activity
🔄 Mar 20 Content change detected
🔄 Mar 15 Content change detected
Does your site score higher than together.ai?
Run the same 40-signal audit on your own domain — free, instant results.
Scan Your Site Free →
🧮 Score Transparency — How is this calculated?
🛡️ Traditional SEO (25% weight)58 × 0.25 = 14.5
🤖 AI Readiness / GEO (40% weight)61 × 0.40 = 24.4
⚡ Performance (20% weight)41 × 0.20 = 8.2
🏗️ Architecture & Trust (15% weight)67 × 0.15 = 10.0
Weighted sum = 14.5 + 24.4 + 8.2 + 10.0
Global SEODiff Score = 57 (D)
📊 ACRI Sub-Scores (AI Readiness Detail)
100
Bot Access
avg 92
97
Rendering
avg 93
40
Structure
avg 35
42
Schema
avg 9
75
Tech Stack
avg 63
🔀
Visibility Delta: Google vs AI
Google (Tranco)
Top 7%
Rank #65216
+11 pts
Gap
AI (ACRI)
Top 17%
Score 76/100

together.ai shows stronger AI visibility than traditional SEO ranking. Great AI foundation to build on. ACRI measures technical crawler readiness. Read the methodology →

Why together.ai ranks here

Tech stackWebflow
Industrydeveloper
RenderingHybrid
Schema coverage1 blocks
Token bloat33.1×

Fastest improvements

  • 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

58/100 25 % of Global Score 🟢 High Confidence

📝 Title Tag

33 chars
Good length

Optimal range: 30–60 characters for SERP display.

📋 Meta Description

147 chars
Good length

Optimal range: 120–160 characters for snippet control.

🔤 Heading Hierarchy

  • ✓ Exactly 1 <h1> tag — found 1
  • ✓ Has <h2> headings — found 6
  • ✓ <h2> not before <h1>

🔍 Indexability

  • ✓ Canonical tag present → https://www.together.ai
  • ✓ 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 — Together AI | The AI Native Cloud
  • ✓ og:description — Build what's next on the AI Native Cloud. Full-stack AI platform for inference, fine-tuning, and GPU clusters — powered by cutting-edge research.
  • ✓ og:image — preview
  • ✓ twitter:card — summary_large_image
📐 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

61/100 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 developer sector, hikkoshizamurai.jp (ACRI: 88) 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 →
together.ai
48
Your ACRI Score
88
Industry Peer ACRI
AI models prioritize pages with strong semantic structure and schema coverage. hikkoshizamurai.jp has schema coverage of 5 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 10%
0% — Safe 50% 100% — Risk
Status Server-Side Rendered (Safe)
Rendering Type Hybrid

📊 Structure & Information Density Docs

Structure Grade 40/100 — Fair
Structured Elements 134 elements (134 lists, 0 rows, 0 headers)
Total Words2803
Raw Density4.8%

🏷️ Schema Health Docs

Organization Schema ✅ Present
Product / Service Schema ⚠️ Not Found
Total Schema Blocks1 block(s) — Basic (low value for AI)

Schema Coverage Map

1/7 schema types detected
✅ Organization
❌ Product/Service
❌ Breadcrumb
❌ FAQ
❌ Article
❌ WebSite
💡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

50
AI Extractability
High
Crawl Cost
None
Blocklist Risk
Extractability50/100 — AI models can partially extract answers from this page
Crawl CostHigh (95/100) — expensive for AI crawlers to process
Blocklist RiskNone — 0 of 5 AI crawlers blocked

Token Bloat Research

3%
🗑️ 97%
Useful Content (19.5 KB)Bloat (627.2 KB)
Token Bloat Ratio33.1× — Bloated

Multimodal Readiness

Visual Context1% Optimized for Vision
Image Alt Coverage2 / 162 images have alt text

TDM Rights

TDM-Reservation HeaderNot set
X-Robots-Tag: noaiNot set
💡Your HTML is 646.7 KB, but only 19.5 KB is text. 3% useful / 97% bloat. AI crawlers have limited context windows (e.g. 128k tokens). This level of bloat (33.1×) risks context-window truncation by ChatGPT, Claude, and Gemini. Reduce inline scripts, CSS, hydration payloads, and tracking code.
💡Only 1% of images have alt text. Add descriptive alt attributes so multimodal AI (ChatGPT Vision) can understand your images.

🔥 Structural Entropy Check Research

0 Entropy
Poor Token Bloat: High
Noise Ratio: 97.0% · SNR: 0.03 · Signal: 4996 / Noise: 160556 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 together.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
Together AI provides a cloud platform for developers and researchers to train, fine-tune, and deploy generative AI models, emphasizing open-source AI and model ownership.
Target Audience
Developers, researchers, AI enthusiasts
Pricing Model
⚠ SEMANTIC VOID
🏆 Competitive Moat
Focus on open-source AI, model ownership, and data privacy differentiates the platform.
📊 Content Depth
6/10
🔄 Programmatic SEO Signals
ProductsSolutionsBlogCareersPricingContactSupport
⚡ Key Pain Points
• Lack of transparency in model training
• Vendor lock-in concerns
Analyzed by SEODiff AI · 2026-03-04

🔧 Tech Stack

FrameworkWebflow
AI-Readiness Score75/100
Servercloudflare
CDNcloudflare
HTTP Status200
Load Time567 ms
Raw HTML Size646.7 KB
Visible Text Size19.5 KB

Performance & Speed

41/100 20 % of Global Score 🟢 High Confidence

⏱️ Time to First Byte

567 ms
Acceptable — room for improvement

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

📦 Page Weight

4138
DOM nodes
647 KB
HTML payload
Heavy page — consider reducing DOM complexity

🗄️ Cache & CDN

  • ✗ Cache-Control header
  • ✓ CDN cache status → HIT
  • ✓ CDN detected → cloudflare

🔬 Tracker Tax

1
tracker scripts
1
third-party domains
0.0%
token overhead
Minimal tracker load — clean signal for bots
amplitude.com
📐 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

67/100 15 % of Global Score 🟢 High Confidence

🗺️ Sitemap & Robots

  • ✓ Sitemap declared in robots.txt → https://www.together.ai/sitemap.xml
  • ✓ Googlebot allowed
  • ✓ GPTBot allowed
  • ✓ ClaudeBot allowed

🔗 Linking

283
internal links
3
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 48/100. Reach 80+ to unlock the green "AI-Verified" badge. Fix the issues below to improve your score.

AI-Verified badge for together.ai
Pending Audit — score below 80 threshold
<a href="https://seodiff.io/radar/domains/together.ai" rel="noopener"><img src="https://seodiff.io/api/v1/badge?domain=together.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 59 pages · Deep-10

Homepage ACRI
48
Single-page score
+6
Consistent readability
Δ delta
Site-Wide ACRI
54
Avg across 59 pages · Range 0–67
Topical Cohesion
14%
Topical Drift
TF-IDF cosine similarity
Total Words
124629
Avg Bloat
37.2×
RAG Fractures [?]
54
⚠️
54 RAG-Chunking Fractures Detected

Poorly formatted tables or pricing grids on 54 pages will be split incorrectly during RAG chunking, causing AI models to hallucinate prices and features.

Page Type ACRI Token Bloat Words Status
https://www.together.ai/blog/coderforge-preview
CoderForge-Preview: SOTA open dataset for training efficient coding agentsTogetherCoder-Preview Data SourcesDataset Comparison - CoderForge-PreviewTrajectories by Task SourceData Generation Cost - TogetherCoder-PreviewTrajectory Length Analysis - TogetherCoder-PreviewSuccess vs Failed Steps - TogetherCoder-PreviewLicense SPDX IdentifiersTraining Sequence Length Analysis - TogetherCoder-PreviewCoderForge Model Benchmarks
pricing 67 15.0× 4336 ⚠️ RAG Fracture
https://www.together.ai/blog/a-practitioners-guide-to-testing-and-running-large-gpu-clusters-for-training-generative-ai-models
A practitioner's guide to testing and running large GPU clusters for training generative AI models
pricing 67 15.2× 3852 ⚠️ RAG Fracture
https://www.together.ai/blog/building-an-autonomous-and-open-data-scientist-agent-from-scratch
From Zero to One: Building An Autonomous and Open Data Scientist Agent from Scratch
pricing 67 12.9× 4514 ⚠️ RAG Fracture
https://www.together.ai/blog/deepcoder
DeepCoder: A Fully Open-Source 14B Coder at O3-mini Level
pricing 67 13.7× 4355 ⚠️ RAG Fracture
https://www.together.ai/blog/deepswe
DeepSWE: Training a Fully Open-sourced, State-of-the-Art Coding Agent by Scaling RL
pricing 67 12.4× 4861 ⚠️ RAG Fracture
https://www.together.ai/blog/even-better-even-faster-quantized-llms-with-qtip
Even Better, Even Faster Quantized LLMs with QTIP
pricing 67 13.4× 4317 ⚠️ RAG Fracture
https://www.together.ai/blog/based
BASED: Simple linear attention language models balance the recall-throughput tradeoff
pricing 64 16.8× 3431 ⚠️ RAG Fracture
https://www.together.ai/blog/adaptive-learning-speculator-system-atlas
AdapTive-LeArning Speculator System (ATLAS): A New Paradigm in LLM Inference via Runtime-Learning AcceleratorsSpeculative Decoding: Performance Analysis
pricing 64 18.7× 3296 ⚠️ RAG Fracture
https://www.together.ai/blog/ai-agents-to-automate-complex-engineering-tasks
How Together AI Uses AI Agents to Automate Complex Engineering Tasks: Lessons from Developing Efficient LLM Inference Systems
pricing 64 16.6× 3419 ⚠️ RAG Fracture
https://www.together.ai/blog/bitdelta
BitDelta: Your Fine-Tune May Only Be Worth One Bit
pricing 64 19.2× 2933 ⚠️ RAG Fracture
https://www.together.ai/blog/cache-aware-disaggregated-inference
Cache-aware prefill–decode disaggregation (CPD) for up to 40% faster long-context LLM serving
pricing 64 17.3× 3244 ⚠️ RAG Fracture
https://www.together.ai/blog/dragonfly-v1
Dragonfly: A large vision-language model with multi-resolution zoom
pricing 64 19.7× 2857 ⚠️ RAG Fracture
https://www.together.ai/blog/evaluate-and-benchmark-llms
How to evaluate and benchmark Large Language Models (LLMs)
pricing 64 16.9× 3389 ⚠️ RAG Fracture
https://www.together.ai/blog/fine-tuning-api-introducing-long-context-training-conversation-data-support-and-more-configuration-options
Fine-tuning API: Introducing long-context training, conversation data support and more configuration options
pricing 64 19.2× 2936 ⚠️ RAG Fracture
https://www.together.ai/blog/alon-gavrielov-as-vp-of-infrastructure-strategy
Together AI welcomes Alon Gavrielov as VP of Infrastructure Strategy
pricing 59 32.0× 1669 ⚠️ RAG Fracture
https://www.together.ai/blog/clustermax-gold
Together AI Awarded ClusterMAX™ Gold Rating by SemiAnalysis
pricing 59 26.9× 2044 ⚠️ RAG Fracture
https://www.together.ai/blog/fastest-inference-for-deepseek-r1-0528-with-nvidia-hgx-b200
Together AI Delivers Top Speeds for DeepSeek-R1-0528 Inference on NVIDIA Blackwell
pricing 59 20.7× 2754 ⚠️ RAG Fracture
https://www.together.ai/blog/code-sandbox-code-interpreter
Introducing Together Code Sandbox & Together Code Interpreter: SOTA code execution for AI
pricing 59 24.1× 2290 ⚠️ RAG Fracture
https://www.together.ai/blog/deepseek-v3-1-hybrid-thinking-model-now-available-on-together-ai
DeepSeek-V3.1: Hybrid Thinking Model Now Available on Together AI
pricing 59 29.2× 1880 ⚠️ RAG Fracture
https://www.together.ai/blog/20-exaflops-gpu-clusters
Growing to 20 exaflops, Together GPU Clusters help startups and enterprises accelerate generative AI development
pricing 59 27.0× 2005 ⚠️ RAG Fracture
Showing 20 of 59 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
/blog/ 49 60 0% 26.3× High JS Bloat
/pricing/ 2 56 0% 60.8× High JS Bloat
/about/ 1 56 0% 122.2× High JS Bloat
/faq/ 1 0 0% 0.0× Low AI Readiness
/docs/ 1 0 0% 0.0× Low AI Readiness
/products/ 1 46 0% 178.8× High JS Bloat
/contact/ 1 36 0% 482.0× High JS Bloat
/integrations/ 1 0 0% 0.0× Low AI Readiness
/case-studies/ 1 0 0% 0.0× Low AI Readiness
/features/ 1 0 0% 0.0× Low AI Readiness
🔗
Outbound External Citations
0 unique external domains cited across 59 pages
support.together.ai ×54
chat.together.ai ×54
whichllm.together.ai ×54
docs.together.ai ×54
api.together.ai ×54
twitter.com ×53
linkedin.com ×53
discord.gg ×53
🔄 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/together.ai

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

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Domains with a similar tech stack, industry, and AI readiness profile to together.ai. Compare side-by-side.

Domain ACRI AI Score Tech Stack Token Bloat Schema
together.ai (this site) 48 76 Webflow 33.1× 1
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📊 Semantic Share of Voice

How often would an AI cite together.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 together.ai. Copy and paste these into your codebase to improve AI visibility. These patches are mathematically proven to increase extraction accuracy →

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": "Together",
  "url": "https://together.ai",
  "potentialAction": {
    "@type": "SearchAction",
    "target": "https://together.ai/search?q={search_term_string}",
    "query-input": "required name=search_term_string"
  }
}
</script>
Reduce Token Bloat
Medium Impact ⏱ 1–2 hrs
Only 3% of your HTML is useful content. AI crawlers waste context window tokens on bloat.
html
<!-- Move inline CSS to external stylesheets -->
<link rel="stylesheet" href="/css/main.css">

<!-- Move inline scripts to external files with defer -->
<script src="/js/app.js" defer></script>

<!-- Remove duplicate navigation blocks -->
<!-- Keep only ONE <nav> in the <header> -->

<!-- Ensure <main> wraps your primary content -->
<main>
  <!-- Your content here — this is what AI sees first -->
</main>
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 Together?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Add your answer here — describe what Together does in 1-2 sentences."
      }
    },
    {
      "@type": "Question",
      "name": "How does Together work?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Explain the key features and how users interact with Together."
      }
    }
  ]
}
</script>
📈

Projected Impact

ROI EST.

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

Current Score
76
Projected Score
88
Improvement
+12 pts
Add WebSite schema +4 pts
Reduce token bloat +5 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
🔍 Found indexing issues?
Run a free deep audit to diagnose crawled-not-indexed, soft 404s, redirect errors, and more.
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