- Visibility17
- Citations2
- Sentiment86
- Site quality87
- AI readiness7
AI assistants name Applied Materials in 10% of answers, the same as the typical company in the technology sector. Its overall score is 38 out of 100, ranking 568th of 2,047 in the study. The company's website passes 1 of 14 technical checks for how ready it is for AI tools.
We asked 15 unbranded questions about the technology market: none named Applied Materials. AI assistants named it in 6 of 60 answers (10.0%). The typical technology company is named in 10.0% of answers. By how often it is named, Applied Materials ranks 132 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
“Best materials engineering technologies for improving chip yield in high-volume fabrication?”
Materials engineering technologies play a critical role in improving chip yield in high-volume semiconductor fabrication by addressing defects, enhancing material properties, and optimizing manufacturing processes. The pursuit of higher yields is crucial because even tiny impurities or defects can lead to significant financial losses, especially with the high cost of advanced wafers.
Key materials engineering technologies and strategies include:
Defect Reduction and Control:
Ultra-pure materials: Impurities in raw materials can drastically affect the performance and relia …
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 0: Not yet agent-ready. Agents struggle to find basic information about the site.
- 2 of robots.txt, Sitemap, Link headers
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 teamHide the checks
- study: 92.0%robots.txtNot met
Publish a valid robots.txt with crawl rules and a Sitemap line.
- study: 86.8%SitemapNot 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 DiscoveryPassed
SVCB or HTTPS records under _agents that advertise agent endpoints.
- 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.txtNot met
Publish an llms.txt with a short summary and the key links.
- study: 93.4%AI bot rulesNot met
Add explicit robots.txt groups for the main AI crawlers.
- 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 AuthNot present
Only relevant if you run your own agents or crawlers: publish a signing key directory.
- study: 0.3%API CatalogNot met
List public APIs in a linkset at /.well-known/api-catalog.
- study: 11.8%OAuth discoveryNot met
Publish OpenID Connect or OAuth server metadata under /.well-known.
- study: 10.3%OAuth Protected ResourceNot met
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 CardNot met
Offer an MCP server and publish its server card under /.well-known.
- study: 0.1%A2A Agent CardNot met
Publish an agent card at /.well-known/agent-card.json.
- study: 0.2%Agent SkillsNot met
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 manifestNot met
Publish an ai-catalog.json listing every agent interface.
Score 3 of 100 · 97% of checks could run · checked on October 5, 2026 · www.appliedmaterials.com · 2,047 companies scanned
1 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
- Not metrobots.txt publishedstudy: 85.0%
- Not metXML sitemapstudy: 73.2%
- Not metHTTP Link headers (RFC 8288)study: 29.0%
- Not metMarkdown content negotiationstudy: 8.3%
- Not metllms.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%
How many times each website was listed as a source in these answers
In the study as S&P 500.
- Do advanced process control systems significantly reduce defect rates in semiconductor fabs?
- Best materials engineering technologies for improving chip yield in high-volume fabrication?
- Alternatives to traditional planar transistor manufacturing in pursuing more efficient chips?
- Is it worth investing in next-generation inspection equipment for chip manufacturing?
- What are the most advanced solutions for semiconductor manufacturing in the US right now?
- How do atomic layer deposition and chemical vapor deposition compare for semiconductor device fabrication?
- What kind of equipment is most suitable for producing OLED and advanced display panels?
- What are the main options besides extreme ultraviolet lithography for advanced node production?
- Typical cost range for US-based semiconductor manufacturing equipment for foundries?
- Which metrology solutions are critical for quality control in logic versus memory chip fabrication?
- What factors impact the total cost of ownership for high-vacuum deposition systems?
- Common causes of reduced line yield in semiconductor wafer processing and how to address them?
- How to identify and minimize particle contamination during photolithography in chip fabrication?
- Wet etch vs dry etch processes in advanced semiconductor manufacturing—what are the key differences?
- Emerging trends in materials engineering for scaling down semiconductor device features?
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/appliedmaterials.com"><img src="https://aeo-audit.rezolve.com/us/badges/appliedmaterials.com.svg" alt="Overall score 38 of 100, US AI Visibility Study 2026" width="280" height="64"></a>