- Visibility11
- Citations4
- Sentiment50
- Site quality80
- AI readiness29
AI assistants name Vertiv in 5% of answers, which matches the typical company in the industrial sector. Its overall score is 31 out of 100, placing it 1,157th of 2,047 companies. The Vertiv website passes 4 out of 14 technical checks that measure how ready it is for AI tools.
We asked 15 unbranded questions about the industrial market: none named Vertiv. AI assistants named it in 3 of 60 answers (5.0%). The typical industrial company is named in 5.0% of answers. By how often it is named, Vertiv ranks 116 of 246 in its sector.
Every dot is a company in the study. Hover one to see it; click to open its report.
This companySame sectorEvery other companyNever named
Five parts, each scored out of 100.
How often AI assistants name the company
How often AI uses the company's own website as a source
How positively AI describes the company
How well built the website's own pages are
How easily AI tools can read and use the website
Visibility is calculated from the answers on this page. How the score is built.
246 companies in this sector. The line on each bar is the typical company.
An answer that names the company
“What are the best digital infrastructure solutions for midsize data centers?”
Below is a practical, vendor-neutral guide to the best digital-infrastructure building blocks and solutions for midsize data centers (roughly tens to a few hundred racks). I’ll cover core areas, why they matter, recommended approaches and typical vendor examples to evaluate, plus a short checklist and rollout advice.
High-level priorities for midsize data centers
Reliability and redundancy appropriate to your SLA (N, N+1, 2N as needed).
Operational simplicity and automation to minimize staff overhead.
Scalability in small, non-disruptive increments.
Cost-efficiency (CapEx and Op …
The AI’s answer as we received it, shortened and not checked for accuracy.
How the mentions in these answers were split between this company and its rivals
Answers naming it, out of answers received
What this website publishes for an AI agent to read, use and buy from, on a scale of six levels.
- 0
- 1
- 2
- 3
- 4
- 5
Level 1: Basic web presence. Two of robots.txt, a sitemap and Link headers are in place.
- Content Signals
Show every check, for your technical teamHide the checks
- study: 92.0%robots.txtPassed
A valid robots.txt with crawl rules at the site root.
- study: 86.8%SitemapPartly met
Serve an XML sitemap and reference it from robots.txt.
- study: 0.3%Link headersNot met
Send Link headers such as rel="api-catalog" or rel="describedby" on the homepage.
- study: 5.5%DNS for AI DiscoveryNot present
Advertise agent endpoints with SVCB records under _agents.
- study: 1.9%Markdown negotiationNot met
Return a markdown version when asked with Accept: text/markdown, for example at the CDN.
- study: 25.1%llms.txtPassed
An llms.txt that tells language models what the site offers.
- study: 93.4%AI bot rulesPassed
Explicit robots.txt rules for AI crawlers such as GPTBot, ClaudeBot and PerplexityBot.
- study: 1.4%Content SignalsNot met
Add a Content-Signal line for search, ai-input and ai-train to robots.txt.
- study: 0.2%Web Bot AuthCould not check
Only relevant if you run your own agents or crawlers: publish a signing key directory.
- study: 0.3%API CatalogCould not check
List public APIs in a linkset at /.well-known/api-catalog.
- study: 11.8%OAuth discoveryCould not check
Publish OpenID Connect or OAuth server metadata under /.well-known.
- study: 10.3%OAuth Protected ResourceCould not check
Serve protected resource metadata at /.well-known/oauth-protected-resource.
- study: 0.0%auth.mdNot met
Publish an auth.md describing how agents sign in.
- study: 0.2%MCP Server CardCould not check
Offer an MCP server and publish its server card under /.well-known.
- study: 0.1%A2A Agent CardCould not check
Publish an agent card at /.well-known/agent-card.json.
- study: 0.2%Agent SkillsCould not check
Publish a skills index with the main tasks agents can do.
- study: 33.7%WebMCPCould not check
Register key actions such as search or cart as WebMCP tools.
- study: 0.1%ARD manifestCould not check
Publish an ai-catalog.json listing every agent interface.
Score 60 of 100 · 65% of checks could run · checked on October 5, 2026 · www.vertiv.com · 2,047 companies scanned
4 of 14 passed. This list is for your technical team. The percentage is how many companies in the study pass each check.
These 14 checks ran during the audit and are what the AI readiness part of the overall score counts. The scan above ran later and is stricter on Link headers and Markdown, so a check can pass here and not there.
Show the 14 checksHide them
- Passedrobots.txt publishedstudy: 85.0%
- Not metXML sitemapstudy: 73.2%
- Not metHTTP Link headers (RFC 8288)study: 29.0%
- Not metMarkdown content negotiationstudy: 8.3%
- Passedllms.txt publishedstudy: 21.7%
- PassedToken budget (page weight)study: 95.2%
- PassedExplicit AI bot rulesstudy: 13.0%
- Not metAPI Catalog (.well-known/api-catalog)study: 0.2%
- Not metOAuth Authorization Server discoverystudy: 10.1%
- Not metOAuth Protected Resource discoverystudy: 9.3%
- Not metMCP Server Cardstudy: 0.0%
- Not metA2A Agent Cardstudy: 0.0%
- Not metWebMCP toolsstudy: 4.2%
- Not metAgent Skills declaredstudy: 0.0%
This website sets rules for 8 AI crawlers by name. All others follow its general rules.
- GPTBot*allowed
- ClaudeBot*allowed
- Anthropic-AIpartly
- Google-Extended*allowed
- Applebot-Extendedpartly
- Meta-ExternalAgentpartly
- FacebookBotpartly
- Bytespiderpartly
- CCBotpartly
- Diffbotpartly
- Omgilibotpartly
- OAI-SearchBot*allowed
- Claude-SearchBot*allowed
- PerplexityBot*allowed
- Applebotpartly
- Amazonbotpartly
- YouBotpartly
- ChatGPT-User*allowed
- Claude-Userpartly
- Perplexity-User*allowed
- DuckAssistBotpartly
- MistralAI-Userpartly
Read from the website’s own rules file (robots.txt). An asterisk marks a crawler the file names. The rest follow its general rules. “Partly” means only some pages are blocked.
How many times each website was listed as a source in these answers
In the study as S&P 500.
- Best practices for deploying AI computing infrastructure in mission-critical environments?
- What are the best digital infrastructure solutions for midsize data centers?
- How do support and maintenance contract costs compare for enterprise-grade UPS systems?
- Is investing in integrated edge data center solutions worth it for small enterprises?
- Are high-capacity busway systems a good option for expanding a data hall?
- What are the most reliable cooling solutions for high-capacity industrial environments?
- What is the typical cost range for pre-engineered modular data center systems in the US?
- UPS systems versus generator-backed solutions: which is more reliable for industrial facilities?
- Alternatives to pre-fabricated edge solutions for managing distributed IT sites?
- How do modular data center solutions compare to traditional build-outs for enterprise IT environments?
- How can overheating and airflow issues be addressed in a high-density rack environment?
- How can remote monitoring be integrated into digital continuity solutions for multi-site operations?
- What are the main alternatives to integrated rack-based infrastructure for scalable data centers?
- Which critical power systems are recommended for communication networks in the US?
- What steps should you take if your power distribution system keeps tripping under load?
Columns, left to right: OpenAI, Claude, Perplexity, Gemini. The AI assistants often disagree. Across the study, on 40% of the questions where a company is named, only one of the four names it.
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<a href="https://aeo-audit.rezolve.com/us/vertiv.com"><img src="https://aeo-audit.rezolve.com/us/badges/vertiv.com.svg" alt="Overall score 31 of 100, US AI Visibility Study 2026" width="280" height="64"></a>