- Visibility43
- Citations2
- Sentiment50
- Site quality87
- AI readiness29
AI assistants name Nvidia in 46.7% of answers, which is much more often than the typical company in the technology sector at 10%. Nvidia's overall score is 42 out of 100, ranking 210th of 2,047 companies. Its website passes 4 out of 14 technical checks for readiness for AI tools.
We asked 15 unbranded questions about the technology market: none named Nvidia. AI assistants named it in 28 of 60 answers (46.7%). The typical technology company is named in 10.0% of answers. By how often it is named, Nvidia ranks 19 of 273 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.
273 companies in this sector. The line on each bar is the typical company.
An answer that names the company
“How can artificial intelligence computing platforms accelerate autonomous vehicle development?”
I'll search for current information on how AI computing platforms are being used to accelerate autonomous vehicle development.Based on current developments, AI computing platforms accelerate autonomous vehicle development in several key ways:
High-Performance Edge Computing
AI computing platforms like NVIDIA DRIVE AGX provide scalable and energy-efficient computing designed to process complex autonomous driving workloads. Modern vehicles require advanced perception and sensor fusion, as well as end-to-end deep learning pipelines that enable comprehensive environment understanding, multimo …
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 2: Bot-aware. Explicit AI bot rules and declared Content Signals.
- Markdown negotiation
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%SitemapPassed
An XML sitemap listing the pages, ideally referenced 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 rulesPartly met
Add explicit robots.txt groups for the main AI crawlers.
- study: 1.4%Content SignalsPassed
Content-Signal lines in robots.txt declaring search, AI input and AI training preferences.
- 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 63 of 100 · 65% of checks could run · checked on October 5, 2026 · www.nvidia.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%
- PassedXML 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%
- Not metExplicit 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 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.
- GPTBotallowed
- ClaudeBotallowed
- Anthropic-AIallowed
- Google-Extendedallowed
- Applebot-Extendedallowed
- Meta-ExternalAgentallowed
- FacebookBotallowed
- Bytespiderallowed
- CCBotallowed
- Diffbotallowed
- Omgilibotallowed
- OAI-SearchBotallowed
- Claude-SearchBotallowed
- PerplexityBotallowed
- Applebotallowed
- Amazonbotallowed
- YouBotallowed
- ChatGPT-Userallowed
- Claude-Userallowed
- Perplexity-Userallowed
- DuckAssistBotallowed
- MistralAI-Userallowed
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.
- How can artificial intelligence computing platforms accelerate autonomous vehicle development?
- Why is my AI training workflow running slow on my current GPU hardware?
- Top high-performance computing solutions for creative professionals in the US
- Common issues when setting up a high-performance computing platform for scientific research
- Alternatives to high-end GPUs for artificial intelligence workloads
- What are some budget-friendly options for creative professionals looking for AI computing power?
- What are the best artificial intelligence computing platforms for researchers and enterprise teams?
- Cloud-based AI computing platforms vs on-premise solutions: which is better for machine learning workloads?
- Non-GPU solutions for high-performance AI computing in research environments
- How do graphics processing units compare to CPUs for deep learning applications?
- Is investing in an enterprise-grade AI computing platform worth it for a midsize business?
- Best AI computing setups for real-time media and broadcast applications
- Are dedicated AI development platforms a good choice for independent developers?
- Typical costs for entry-level vs enterprise-grade artificial intelligence computing platforms
- What factors influence the price of AI computing hardware in the United States?
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/nvidia.com"><img src="https://aeo-audit.rezolve.com/us/badges/nvidia.com.svg" alt="Overall score 42 of 100, US AI Visibility Study 2026" width="280" height="64"></a>