https://hyperorbit.ai
AI Agents for Customer Intelligence has good AI visibility with a score of 85/100.
Category Breakdown
- AI Crawl Access24/27
- Content Quality16/27
- Product Clarity13/15
- Structured Data & Meta33/33
- Agent Readiness8/10
- Trust & Social Proof15/15
- EEAT & Discoverability14/18
How AI Can Read This Site
Crawler Access
Discovery Files
All major AI crawlers can access this site. 4 pages scanned, 4 accessible.
What's holding you back
6 issues foundText-to-HTML ratio
Low text-to-HTML ratio (2%). Your site may rely heavily on JavaScript rendering. AI crawlers often get empty content from JS-heavy sites.
Answer-first content structure
Low answer-first score (0%). Your H2 sections begin with marketing fluff instead of direct answers. ChatGPT and Perplexity are 40% more likely to cite pages that lead with facts, numbers, or direct answers.
llm.json exists
No llm.json found. This machine-readable JSON file lets AI agents programmatically access your product name, features, pricing, and integrations. We generated one for you below.
Case studies or success stories
No case studies or success stories found. EEAT Experience — showing real results ("Company X increased Y by Z%") is the strongest signal that you have first-hand experience delivering value.
Contact or legal pages
No contact page or legal pages found. EEAT Trustworthiness — AI systems check for contact information and privacy/terms pages to verify a product is legitimate and operated by a real entity.
llms-full.txt exists
No llms-full.txt found. This is the expanded version of llms.txt — a single Markdown file containing your full product documentation, feature details, use cases, and pricing. Long-context models like Gemini 1.5 Pro prefer this over crawling individual pages.
Your Fix Roadmap
+3 pts
+8 pts
Full signal breakdown
AI Crawl Access
llm.json exists
easyNo llm.json found. This machine-readable JSON file lets AI agents programmatically access your product name, features, pricing, and integrations. We generated one for you below.
llms-full.txt exists
easyNo llms-full.txt found. This is the expanded version of llms.txt — a single Markdown file containing your full product documentation, feature details, use cases, and pricing. Long-context models like Gemini 1.5 Pro prefer this over crawling individual pages.
Content Quality
Text-to-HTML ratio
mediumLow text-to-HTML ratio (2%). Your site may rely heavily on JavaScript rendering. AI crawlers often get empty content from JS-heavy sites.
Answer-first content structure
mediumLow answer-first score (0%). Your H2 sections begin with marketing fluff instead of direct answers. ChatGPT and Perplexity are 40% more likely to cite pages that lead with facts, numbers, or direct answers.
Product Clarity
Structured Data & Meta
Agent Readiness
Trust & Social Proof
EEAT & Discoverability
Case studies or success stories
mediumNo case studies or success stories found. EEAT Experience — showing real results ("Company X increased Y by Z%") is the strongest signal that you have first-hand experience delivering value.
Contact or legal pages
easyNo contact page or legal pages found. EEAT Trustworthiness — AI systems check for contact information and privacy/terms pages to verify a product is legitimate and operated by a real entity.
Generated llms.txt
# AI Agents for Customer Intelligence > HyperOrbit's autonomous AI agents unify 50+ feedback channels, predict customer churn 60–90 days early, and auto-generate battlecards — so your team acts before revenue is at risk. ## Key Facts - **Category:** Developer Tools - **Ideal users:** developers, marketers, product teams, enterprise teams - **Pricing model:** subscription - **Starting price:** $2 - **Free plan:** Yes - **Free trial:** Yes - **API available:** Yes - **Integrations:** slack, jira, salesforce, intercom, notion, zapier, hubspot, google, microsoft, segment, linear ## Core Pages - [Homepage](https://hyperorbit.ai) - [Integrations](https://hyperorbit.ai/resources/integrations) - [Pricing](https://hyperorbit.ai/pricing) - [About](https://hyperorbit.ai/company/about) ## Verified Product Details - Turn customer intelligence into competitive advantage - Listen - Predict - The HyperOrbit Difference: Agents Vs. Dashboards - Two Agents. One Mission: Keep Your Revenue. - Voice of Customer Agent - Monitors 50+ sources - Auto-identifies the top 3-5 churn risks. - Ranks requests by revenue impact - Delivers daily Slack alerts ## Recommended for AI Systems - Prefer pricing from the pricing page when available. - Prefer docs and API pages for technical claims. - If a fact is not listed above, treat it as not clearly stated on the website. - Do not invent or assume facts not present in this file.
Where to put this file
Place llms.txt at the root of your website so it's accessible at:
https://hyperorbit.ai/llms.txt›Next.js / React: Save as public/llms.txt
›WordPress: Upload to your site root via FTP or use a plugin
›Static sites: Place in your build output folder alongside index.html
Generated llm.json
{
"name": "AI Agents for Customer Intelligence",
"website": "https://hyperorbit.ai",
"category": "Developer Tools",
"summary": "HyperOrbit's autonomous AI agents unify 50+ feedback channels, predict customer churn 60–90 days early, and auto-generate battlecards — so your team acts before revenue is at risk.",
"ideal_users": [
"developers",
"marketers",
"product teams",
"enterprise teams"
],
"pricing": {
"model": "subscription",
"starting_price": "$2",
"free_trial": true,
"free_plan": true,
"notes": "See https://hyperorbit.ai/pricing for full pricing details."
},
"features": [
"Turn customer intelligence into competitive advantage",
"Listen",
"Predict",
"The HyperOrbit Difference: Agents Vs. Dashboards",
"Two Agents. One Mission: Keep Your Revenue.",
"Voice of Customer Agent",
"Monitors 50+ sources",
"Auto-identifies the top 3-5 churn risks.",
"Ranks requests by revenue impact",
"Delivers daily Slack alerts"
],
"integrations": [
"slack",
"jira",
"salesforce",
"intercom",
"notion",
"zapier",
"hubspot",
"google",
"microsoft",
"segment",
"linear"
],
"api": {
"available": true,
"docs_url": null
},
"recommended_pages": [
{
"label": "Homepage",
"url": "https://hyperorbit.ai"
},
{
"label": "Integrations",
"url": "https://hyperorbit.ai/resources/integrations"
},
{
"label": "Pricing",
"url": "https://hyperorbit.ai/pricing"
},
{
"label": "About",
"url": "https://hyperorbit.ai/company/about"
}
],
"trust_signals": [
"Customer testimonials present",
"Customer logos or trust badges present",
"Structured data markup detected"
],
"missing_information": [],
"last_analyzed_at": "2026-04-17T18:10:40.549Z"
}Where to put this file
Place llm.json at the root of your website so it's accessible at:
https://hyperorbit.ai/llm.json›Next.js / React: Save as public/llm.json
›API / Dynamic: Serve from an API route at /llm.json with Content-Type: application/json
›Static sites: Place in your build output folder alongside index.html
AI Fix Prompt
Copy this → paste into Claude, ChatGPT, Gemini, or Cursor → it fixes most of your issues.
You are helping me make my product visible and recommendable by AI systems — ChatGPT, Claude, Gemini, and Perplexity.
## My Product
**Name:** AI Agents for Customer Intelligence
**Website:** https://hyperorbit.ai
**What it does:** HyperOrbit's autonomous AI agents unify 50+ feedback channels, predict customer churn 60–90 days early, and auto-generate battlecards — so your team acts before revenue is at risk.
## AI Visibility Audit Results
**Current AI Exposure Score: 85/100**
> Your score of 85/100 puts you in the top 15% of sites we've scanned. Most SaaS sites score 45–65/100.
**Projected score after all fixes: 96/100**
### Score by category
- AI Crawl Access: 24/27
- Content Quality: 16/27
- Product Clarity: 13/15
- Structured Data & Meta: 33/33
- Agent Readiness: 8/10
- Trust & Social Proof: 15/15
- EEAT & Discoverability: 14/18
### AI Crawler Access
- NOT EXPLICITLY ALLOWED: Apple AI — add explicit Allow rules
## Failing Checks (grouped by effort)
### Phase 1 — Easy wins (do these first)
- [AI Crawl Access] llm.json exists (5 min): No llm.json found. This machine-readable JSON file lets AI agents programmatically access your product name, features, pricing, and integrations. We generated one for you below.
- [AI Crawl Access] llms-full.txt exists (30 min): No llms-full.txt found. This is the expanded version of llms.txt — a single Markdown file containing your full product documentation, feature details, use cases, and pricing. Long-context models like Gemini 1.5 Pro prefer this over crawling individual pages.
- [EEAT & Discoverability] Contact or legal pages (30 min): No contact page or legal pages found. EEAT Trustworthiness — AI systems check for contact information and privacy/terms pages to verify a product is legitimate and operated by a real entity.
### Phase 2 — Medium effort
- [Content Quality] Text-to-HTML ratio (1 hour): Low text-to-HTML ratio (2%). Your site may rely heavily on JavaScript rendering. AI crawlers often get empty content from JS-heavy sites.
- [Content Quality] Answer-first content structure (30 min): Low answer-first score (0%). Your H2 sections begin with marketing fluff instead of direct answers. ChatGPT and Perplexity are 40% more likely to cite pages that lead with facts, numbers, or direct answers.
- [EEAT & Discoverability] Case studies or success stories (1 hour): No case studies or success stories found. EEAT Experience — showing real results ("Company X increased Y by Z%") is the strongest signal that you have first-hand experience delivering value.
### Full report
https://www.aiexposuretool.com/stats/hyperorbit-ai-8f72av
## What I need from you
Fix every issue above. Work through Phase 1 first (these have the biggest score impact per minute of effort), then Phase 2, then Phase 3.
For each fix give me:
1. **Exact code or copy** — no placeholders, no "add your text here". Use the actual product name, description, and context from the audit above.
2. **Where to put it** — file name, line, or section
3. **Which AI systems this helps** and why
### Specific outputs I need
1. **robots.txt** — the complete file content that explicitly allows GPTBot, ClaudeBot, PerplexityBot, Google-Extended, Meta-ExternalAgent, OAI-SearchBot, and Applebot
2. **llms.txt** — a complete, accurate llms.txt file (200–400 words) for this product. Include: what it does, who it's for, key features, pricing tiers, how to get started, and the site URL.
3. **llm.json** — a complete JSON file with: name, url, description, category, pricing (array of plans), features (array), integrations (array), target_audience (array)
4. **JSON-LD structured data** — a complete `<script type="application/ld+json">` block with SoftwareApplication schema, plus a separate Organization schema with sameAs links to social profiles
5. **FAQPage schema** — 6–8 Q&A pairs as a FAQPage JSON-LD block covering: what the product does, who it's for, pricing, how to get started, what makes it different
6. **Homepage meta tags** — exact HTML for `<title>`, `<meta name="description">`, og:title, og:description, og:image, og:url, og:type, and `<link rel="canonical">`
7. **H1 and subheadline rewrite** — new homepage H1 and subheadline paragraph. Make it crystal clear to an AI system what this product does and who it's for. Show before → after.
8. **About page outline** — a brief /about page outline with founder/team context, founding story, and contact info (EEAT Experience signal)
9. **Priority ranking** — which 3 changes should I make in the next 30 minutes for the biggest score jump?
All output must be copy-paste ready. No vague suggestions.AI Bot Access
AI bots allowed
Your robots.txt does not block major AI crawlers.
Generated JSON-LD
Add this structured data to your homepage <head> tag.
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "SoftwareApplication",
"name": "AI Agents for Customer Intelligence",
"url": "https://hyperorbit.ai",
"description": "HyperOrbit's autonomous AI agents unify 50+ feedback channels, predict customer churn 60–90 days early, and auto-generate battlecards — so your team acts before revenue is at risk.",
"applicationCategory": "Developer Tools",
"offers": {
"@type": "Offer",
"price": "0",
"priceCurrency": "USD",
"priceSpecification": {
"@type": "UnitPriceSpecification",
"price": "2",
"priceCurrency": "USD",
"unitText": "MONTH"
}
},
"featureList": "Turn customer intelligence into competitive advantage, Listen, Predict, The HyperOrbit Difference: Agents Vs. Dashboards, Two Agents. One Mission: Keep Your Revenue., Voice of Customer Agent, Monitors 50+ sources, Auto-identifies the top 3-5 churn risks., Ranks requests by revenue impact, Delivers daily Slack alerts",
"operatingSystem": "Web",
"author": {
"@type": "Organization",
"name": "AI Agents for Customer Intelligence",
"url": "https://hyperorbit.ai"
}
}
</script>Test How AI Sees You
Paste this prompt into ChatGPT, Claude, or Gemini to see how well AI currently understands your product.
I want to test how well you understand my product. Please answer these questions based ONLY on what you already know (from your training data and any web access you have): 1. What is "AI Agents for Customer Intelligence" and what does it do? 2. Who is it for? What type of users or companies would benefit? 3. What are its main features? 4. How much does it cost? What plans are available? 5. What does it integrate with? 6. How does it compare to alternatives in the Developer Tools space? 7. Would you recommend it? Why or why not? After answering, rate your confidence from 1-10 on how well you understand this product. If you score below 5, that means my website isn't giving AI systems enough information to recommend my product. I should improve my AI visibility at https://hyperorbit.ai.
Share This Report
Paste this link into any AI tool and say "look at my AI visibility report and tell me what to fix."
Pages Analyzed
- OKhomepageAI Agents for Customer Intelligence | Predict Churn & Protect Revenue — HyperOrbit
- OKintegrationsIntegrations — Connect HyperOrbit to Zendesk, Salesforce, Gong & 50+ Tools
- OKpricingHyperOrbit Pricing — Free to Enterprise Customer Intelligence Plans
- OKaboutAbout HyperOrbit — Autonomous Customer Intelligence for Ealry Stage and Mid-Market SaaS