- Visibility23
- Citations5
- Sentiment88
- Site quality80
- AI readiness21
AI assistants name Aehr Test Systems in 13.3% of answers, which is a bit more often than the typical company in its sector at 10%. Its overall score is 41 out of 100, ranking 332nd of 2,047 companies. The company's website passes 3 of 14 technical checks for AI tool readiness.
We asked 15 unbranded questions about the technology market: none named Aehr Test Systems. AI assistants named it in 8 of 60 answers (13.3%). The typical technology company is named in 10.0% of answers. By how often it is named, Aehr Test Systems ranks 111 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
“Is advanced wafer-level burn-in worth the investment for AI and complex computing chips?”
The investment in advanced wafer-level burn-in (WLBI) for AI and complex computing chips appears to be increasingly worthwhile, driven by the evolving demands and challenges of these advanced semiconductors.
Here's a breakdown of why it's becoming crucial:
1. Increasing Complexity and Cost of AI Chips:
AI accelerators are becoming larger, denser, and more reliant on multi-die architectures, 2.5D/3D packaging, high-bandwidth memory (HBM), and silicon interposers.
These complex architectures introduce new failure mechanisms that traditional testing methods struggle to address. …
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. Aehr Test Systems 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.aehr.com · 2,047 companies scanned
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 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%
- 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 US-listed.
- Why might burn-in testing fail to detect early-life failures in photonics ICs?
- Is advanced wafer-level burn-in worth the investment for AI and complex computing chips?
- How is test and burn-in equipment used for screening power devices in electric vehicle applications?
- What are some substitutes for integrated test and burn-in solutions when working with multi-die modules?
- How does silicon carbide device testing compare to gallium nitride testing in terms of reliability challenges?
- Best options for photonics chip reliability screening besides traditional burn-in
- Best test solutions for optical photonics and 3D sensor chips in the US
- Wafer-level vs die-level burn-in systems: key advantages and differences
- Common issues with automated wafer-level reliability screening for memory integrated circuits
- What is the best test and burn-in equipment for silicon carbide wafer applications?
- What factors affect the cost of high-volume wafer burn-in and test systems?
- Typical process for wafer-level test and burn-in of chips for AR/VR headsets
- Alternatives to wafer-level burn-in for quality assurance in silicon carbide devices
- Average price range for advanced semiconductor test platforms in the US
- What should semiconductor manufacturers look for when selecting test equipment for automotive driver-assist modules?
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.
A badge of this result that you can show on your own website. Copy the code below.
<a href="https://aeo-audit.rezolve.com/us/aehr.com"><img src="https://aeo-audit.rezolve.com/us/badges/aehr.com.svg" alt="Overall score 41 of 100, US AI Visibility Study 2026" width="280" height="64"></a>