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NetApp

netapp.com · Technology · NTAP

Ranked 746 of 2,047 companies in the study

36Overall score
  • Visibility17
  • Citations2
  • Sentiment67
  • Site quality80
  • AI readiness36
What this means for NetApp

AI assistants name NetApp in 11.7% of answers, which is slightly more often than the typical company in its sector. NetApp has an overall score of 36 out of 100, ranking 746th of 2,047 companies. Its website passes 5 of 14 technical checks for AI tool readiness.

We asked 15 unbranded questions about the technology market: none named NetApp. AI assistants named it in 7 of 60 answers (11.7%). The typical technology company is named in 10.0% of answers. By how often it is named, NetApp ranks 121 of 273 in its sector.

Named by AI in
11.7%
7 of 60 answers
Share of mentions
24.1%
compared with 5 rivals
AI readiness
5/14
technical checks passed. Typical for its sector: 4
Rank in its sector
126 of 273
by overall score, where the typical technology company scores 36
How NetApp compares with all 2,047 companies

Every dot is a company in the study. Hover one to see it; click to open its report.

This companySame sectorEvery other companyNever named

What makes up the score

Five parts, each scored out of 100.

Visibility
17

How often AI assistants name the company

Citations
2

How often AI uses the company's own website as a source

Sentiment
67

How positively AI describes the company

Site quality
80

How well built the website's own pages are

AI readiness
36

How easily AI tools can read and use the website

Visibility is calculated from the answers on this page. How the score is built.

Compared with technology

273 companies in this sector. The line on each bar is the typical company.

Overall score36
Ranks 126 of 273. Typical company: 36
Named in answers12%
Ranks 121 of 273. Typical company: 10%
AI readiness36
Ranks 36 of 273. Typical company: 29
What Gemini actually said

An answer that names the company

“What are some alternatives to traditional SAN and NAS solutions for high-performance enterprise storage?”

For high-performance enterprise storage, several alternatives to traditional SAN (Storage Area Network) and NAS (Network Attached Storage) solutions have emerged. These newer approaches offer enhanced scalability, flexibility, and efficiency, particularly for modern workloads like AI/ML, big data analytics, and cloud-native applications.

Here are some of the key alternatives:

Software-Defined Storage (SDS): SDS decouples the storage software from the underlying hardware, providing greater flexibility and eliminating vendor lock-in. It allows for independent scaling of capacity and pe …

The AI’s answer as we received it, shortened and not checked for accuracy.

Also named
Pure Storage7
Share of mentions

How the mentions in these answers were split between this company and its rivals

NetApp
29.2%
Dell Technologies (Dell EMC)
29.2%
Pure Storage
20.8%
IBM Storage
20.8%
Hitachi Vantara
0.0%
HPE (Hewlett Packard Enterprise) Storage
0.0%
Which AI assistants named the company

Answers naming it, out of answers received

Gemini
2/15
Perplexity
2/15
Claude
2/15
OpenAI
1/15
Ready for AI agents

What this website publishes for an AI agent to read, use and buy from, on a scale of six levels.

  1. 0
  2. 1
  3. 2
  4. 3
  5. 4
  6. 5

Level 1: Basic web presence. Two of robots.txt, a sitemap and Link headers are in place.

To reach level 2:
  • Content Signals

The website turns away requests that do not come from a browser. AI agents that say what they are meet the same refusal.

Show every check, for your technical team
Discoverability
77 of 100
  • robots.txtPassed

    A valid robots.txt with crawl rules at the site root.

    study: 92.0%
  • SitemapPassed

    An XML sitemap listing the pages, ideally referenced from robots.txt.

    study: 86.8%
  • Link headersNot met

    Send Link headers such as rel="api-catalog" or rel="describedby" on the homepage.

    study: 0.3%
  • DNS for AI DiscoveryNot present

    Advertise agent endpoints with SVCB records under _agents.

    study: 5.5%
Content accessibility
25 of 100
  • Markdown negotiationNot met

    Return a markdown version when asked with Accept: text/markdown, for example at the CDN.

    study: 1.9%
  • llms.txtPartly met

    Publish an llms.txt with a short summary and the key links.

    study: 25.1%
Bot access control
32 of 100
  • AI bot rulesPartly met

    Add explicit robots.txt groups for the main AI crawlers.

    study: 93.4%
  • Content SignalsNot met

    Add a Content-Signal line for search, ai-input and ai-train to robots.txt.

    study: 1.4%
  • Web Bot AuthCould not check

    Only relevant if you run your own agents or crawlers: publish a signing key directory.

    study: 0.2%
APIs, auth and MCP
0 of 100
  • API CatalogNot met

    List public APIs in a linkset at /.well-known/api-catalog.

    study: 0.3%
  • OAuth discoveryNot met

    Publish OpenID Connect or OAuth server metadata under /.well-known.

    study: 11.8%
  • OAuth Protected ResourceNot met

    Serve protected resource metadata at /.well-known/oauth-protected-resource.

    study: 10.3%
  • auth.mdNot met

    Publish an auth.md describing how agents sign in.

    study: 0.0%
  • MCP Server CardNot met

    Offer an MCP server and publish its server card under /.well-known.

    study: 0.2%
  • A2A Agent CardNot met

    Publish an agent card at /.well-known/agent-card.json.

    study: 0.1%
  • Agent SkillsNot met

    Publish a skills index with the main tasks agents can do.

    study: 0.2%
  • WebMCPCould not check

    Register key actions such as search or cart as WebMCP tools.

    study: 33.7%
  • ARD manifestNot met

    Publish an ai-catalog.json listing every agent interface.

    study: 0.1%

Score 31 of 100 · 94% of checks could run · checked on October 5, 2026 · www.netapp.com · 2,047 companies scanned

See how every company did, and how this was measured.

The checks behind the AI readiness score

5 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 checks
Discoverability
  • Passedrobots.txt publishedstudy: 85.0%
  • PassedXML sitemapstudy: 73.2%
  • PassedHTTP Link headers (RFC 8288)study: 29.0%
Content Accessibility
  • Not metMarkdown content negotiationstudy: 8.3%
  • Passedllms.txt publishedstudy: 21.7%
  • PassedToken budget (page weight)study: 95.2%
Bot Access Control
  • Not metExplicit AI bot rulesstudy: 13.0%
API / Auth / MCP
  • 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%
What AI crawlers may read (robots.txt)

This website sets no rules for any AI crawler by name, like 84% of the websites whose rules we could read. Every AI crawler follows its general rules.

Training AI
  • GPTBotpartly
  • ClaudeBotpartly
  • Anthropic-AIpartly
  • Google-Extendedpartly
  • Applebot-Extendedpartly
  • Meta-ExternalAgentpartly
  • FacebookBotpartly
  • Bytespiderpartly
  • CCBotpartly
  • Diffbotpartly
  • Omgilibotpartly
AI search
  • OAI-SearchBotpartly
  • Claude-SearchBotpartly
  • PerplexityBotpartly
  • Applebotpartly
  • Amazonbotpartly
  • YouBotpartly
Answering questions
  • ChatGPT-Userpartly
  • Claude-Userpartly
  • Perplexity-Userpartly
  • 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.

Websites the AI used as sources

How many times each website was listed as a source in these answers

cloudian.com
37
techtarget.com
28
ibm.com
27
netapp.com (its own website)
15
dell.com
15
solved.scality.com
11
wasabi.com
10
min.io
9
everpuredata.com
9
stonefly.com
8

In the study as S&P 500.

Every question, and where the company came up (5 of 15)
QuestionOpenAIClaudePerplexityGemini
  • Is it cheaper to build on-premises intelligent data infrastructure or rely on cloud-based services?
  • What are some alternatives to traditional SAN and NAS solutions for high-performance enterprise storage?
  • Is investing in intelligent data infrastructure worth it for a company scaling its AI initiatives?
  • How can organizations address bottlenecks in their current enterprise storage systems?
  • What should I consider before purchasing enterprise-grade data storage for a U.S.-based organization?
  • Enterprise data storage vs cloud-native storage: which is better for managing large-scale AI datasets?
  • How can enterprise data storage be used to accelerate machine learning model training?
  • How does all-flash storage compare to hybrid storage arrays for enterprise use?
  • Which advanced data infrastructure platforms are recommended for large enterprises focused on innovation?
  • How are enterprise data storage solutions typically priced for large-scale deployments in the U.S.?
  • What steps can I take if our data infrastructure is struggling to support AI workloads?
  • Which next-generation data platforms can replace legacy infrastructure for AI-focused organizations?
  • What type of data infrastructure best supports real-time analytics in large organizations?
  • What are the best enterprise data storage solutions for organizations deploying AI workloads?
  • What features should I look for in an enterprise data management platform to support future growth?
named the companyanswered without naming itdid not answer

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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Overall score 36 of 100 badge for NetApp

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