- Visibility19
- Citations3
- Sentiment50
- Site quality80
- AI readiness29
AI assistants name KLA in 10% of answers, which matches how often the typical company in the technology sector is named. KLA's overall score is 33 out of 100, ranking it 969th of 2,047 companies. Its website passes 4 out of 14 technical checks for being ready for AI tools.
We asked 15 unbranded questions about the technology market: none named KLA. 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, KLA 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
“How do optical inspection systems compare to electron beam inspection systems in semiconductor production?”
Short answer
Optical inspection (OI) uses light; it’s fast, non‑destructive, and excellent for high‑throughput whole‑wafer scanning and finding many common defects.
Electron‑beam inspection (EBI) uses a focused electron beam; it gives much higher sensitivity and better resolution for very small or low‑contrast defects but is slower, more expensive, and more complex to integrate.
Use OI for broad, fast monitoring and yield‑screening; use EBI when you need root‑cause analysis, to detect the smallest or electrically relevant defects, or to inspect advanced nodes with features that are opt …
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
Not by itself. KLA publishes none of the purchase protocols we look for. An agent would have to click through the checkout like a person.
- UCPNot present
- ACPNot present
- AP2Not present
- x402Not present
- MPPNot present
The shop runs on WooCommerce.
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.txtNot met
Publish an llms.txt with a short summary and the key links.
- study: 93.4%AI bot rulesPartly 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 25 of 100 · 97% of checks could run · checked on October 5, 2026 · www.kla.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%
- PassedHTTP 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%
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.
- GPTBotpartly
- ClaudeBotpartly
- Anthropic-AIpartly
- Google-Extendedpartly
- Applebot-Extendedpartly
- Meta-ExternalAgentpartly
- FacebookBotpartly
- Bytespiderpartly
- CCBotpartly
- Diffbotpartly
- Omgilibotpartly
- OAI-SearchBotpartly
- Claude-SearchBotpartly
- PerplexityBotpartly
- Applebotpartly
- Amazonbotpartly
- YouBotpartly
- 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.
How many times each website was listed as a source in these answers
In the study as S&P 500.
- Are there cost-effective alternatives to proprietary process control software for semiconductor fabs?
- What can cause inconsistent measurements in semiconductor metrology equipment?
- How do optical inspection systems compare to electron beam inspection systems in semiconductor production?
- Do advanced analytics platforms make a significant difference in semiconductor defect detection?
- Which types of inspection tools are essential for advanced semiconductor manufacturing?
- What are the best process control systems for improving wafer yield in semiconductor fabs?
- How are process control systems used to monitor critical dimensions in sub-10nm semiconductor manufacturing?
- How do support and maintenance costs impact the total cost of ownership for advanced metrology tools?
- Metrology tools vs defect inspection tools: which is more critical for process control in chip fabrication?
- What price range should semiconductor fabs expect for cutting-edge inspection systems?
- What role does computational analytics play in predicting yield loss in semiconductor production?
- Are high-end process control solutions worth the investment for a mid-sized semiconductor manufacturer?
- What are the main alternatives to traditional in-line inspection systems for process monitoring?
- How do you address false positives in wafer inspection results?
- Which non-destructive analysis methods are commonly used in semiconductor yield management?
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/kla.com"><img src="https://aeo-audit.rezolve.com/us/badges/kla.com.svg" alt="Overall score 33 of 100, US AI Visibility Study 2026" width="280" height="64"></a>