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National Oilwell Varco

nov.com · Technology · NOV

Ranked 587 of 2,047 companies in the study

38Overall score
  • Visibility10
  • Citations0
  • Sentiment100
  • Site quality80
  • AI readiness21
What this means for National Oilwell Varco

AI assistants name National Oilwell Varco in 6.7% of answers, which is less often than the typical company in the Technology sector at 10%. Its overall score is 38 out of 100, ranking 587th of 2,047 companies. The company's website passes 3 of 14 technical checks measuring readiness for AI tools.

We asked 15 unbranded questions about the technology market: none named National Oilwell Varco. AI assistants named it in 4 of 60 answers (6.7%). The typical technology company is named in 10.0% of answers. By how often it is named, National Oilwell Varco ranks 165 of 273 in its sector.

Named by AI in
6.7%
4 of 60 answers
Share of mentions
14.8%
compared with 5 rivals
AI readiness
3/14
technical checks passed. Typical for its sector: 4
Rank in its sector
89 of 273
by overall score, where the typical technology company scores 36
How National Oilwell Varco 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
10

How often AI assistants name the company

Citations
0

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

Sentiment
100

How positively AI describes the company

Site quality
80

How well built the website's own pages are

AI readiness
21

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 score38
Ranks 89 of 273. Typical company: 36
Named in answers7%
Ranks 165 of 273. Typical company: 10%
AI readiness21
Ranks 161 of 273. Typical company: 29
What Gemini actually said

An answer that names the company

“Typical cost range for rig automation systems for mid-sized operators”

The typical cost range for rig automation systems for mid-sized operators can vary significantly based on the level of integration and the type of rig. Upgrading a single land rig to fully automated systems generally costs between $2.5 million and $6 million.

Key factors influencing the cost include:

Level of Automation: Basic digital control systems can be retrofitted to existing equipment for less than $150,000, offering benefits like faster drilling and reduced downtime. More advanced systems, such as AI-based predictive systems, can cost upwards of $800,000 per rig for installatio …

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

Also named
TechnipFMC4Halliburton4Baker Hughes4National Oilwell Varco (NOV)1
Share of mentions

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

National Oilwell Varco
18.2%
Baker Hughes
18.2%
Halliburton
18.2%
TechnipFMC
18.2%
Schlumberger (SLB)
13.6%
Weatherford
13.6%
Which AI assistants named the company

Answers naming it, out of answers received

Gemini
2/15
Perplexity
1/15
OpenAI
1/15
Claude
0/15
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
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
0 of 100
  • Markdown negotiationNot met

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

    study: 1.9%
  • llms.txtNot 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 AuthNot present

    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 25 of 100 · 97% of checks could run · checked on October 5, 2026 · www.nov.com · 2,047 companies scanned

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

The checks behind the AI readiness score

3 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%
  • Not metHTTP Link headers (RFC 8288)study: 29.0%
Content Accessibility
  • Not metMarkdown content negotiationstudy: 8.3%
  • Not metllms.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

slb.com
15
image-ppubs.uspto.gov
13
offshore-mag.com
12
energy.gov
11
jpt.spe.org
9
bakerhughes.com
9
sciencedirect.com
9
en.wikipedia.org
8
worldoil.com
8
marketintelo.com
8

In the study as US-listed.

Every question, and where the company came up (2 of 15)
QuestionOpenAIClaudePerplexityGemini
  • Lower-cost substitutes for advanced horizontal drilling technologies
  • Typical cost range for rig automation systems for mid-sized operators
  • What factors influence the price of customized oilfield equipment in the US?
  • Best equipment for boosting oil recovery in mature fields
  • Is investing in advanced drilling technologies worth it for small energy companies?
  • Do modular drilling rigs provide better value for expanding operations?
  • What are the main alternatives to traditional fixed platforms in offshore oil extraction?
  • Top technology solutions for improving efficiency in the energy sector
  • Recommended energy technology solutions for geothermal power projects
  • Troubleshooting frequent failures in deepwater flow assurance solutions
  • How does land rig equipment differ from offshore drilling systems?
  • What are the best oilfield equipment providers for offshore drilling projects?
  • Alternatives to conventional wellhead systems for enhanced safety
  • Common problems with hydraulic fracturing equipment and how to fix them
  • Oilfield automation vs traditional manual operations: which is more cost-effective?
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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