- Visibility10
- Citations1
- Sentiment50
- Site quality93
- AI readiness21
AI assistants name Micron Technology in 6.7% of answers, which is less often than the typical company in the technology sector. Its overall score is 31 out of 100, ranking 1,134th of 2,047 across all companies. The company's website passes 3 out of 14 technical checks for readiness with AI tools.
We asked 15 unbranded questions about the technology market: none named Micron Technology. 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, Micron Technology ranks 165 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 DDR5 memory module prices compare to DDR4 in the US market?”
In the US market, DDR5 memory modules are significantly more expensive than DDR4, with prices having increased dramatically over the past year for both, though DDR5 has seen a much steeper rise. This gap is influenced by factors like increased demand for DDR5 in new systems and a shift in manufacturing focus towards High Bandwidth Memory (HBM) and DDR5 for AI applications.
Here's a more detailed comparison:
Price Difference and Trends:
Overall Cost: DDR4 is considerably cheaper per gigabyte than DDR5. For instance, a 32GB DDR4-3200 kit might cost around $250, while a comparable 3 …
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
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%WebMCPNot met
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 24 of 100 · 100% of checks could run · checked on October 4, 2026 · www.micron.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 S&P 500.
- Are enterprise-grade NVMe drives worth the investment for large organizations?
- How do DDR5 memory module prices compare to DDR4 in the US market?
- Top options for enterprise storage used in cloud computing environments?
- How does SSD performance compare to HDD for machine learning tasks?
- Common issues with enterprise SSD reliability in virtualized environments?
- What type of storage is recommended for hybrid cloud deployments?
- Best memory options to support real-time analytics in the enterprise?
- Is it necessary to choose high-end memory modules for AI inference servers?
- What are the main non-volatile memory technologies available for edge computing?
- Why is my server experiencing latency with high-density memory modules?
- Alternatives to traditional DRAM for AI model training?
- SLC vs MLC NAND: Pros and cons for compute-intensive workloads?
- What factors influence the cost of enterprise solid-state drives?
- DRAM vs NAND flash: Which is better for data center applications?
- What are the best high-performance memory solutions for AI workloads?
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/micron.com"><img src="https://aeo-audit.rezolve.com/us/badges/micron.com.svg" alt="Overall score 31 of 100, US AI Visibility Study 2026" width="280" height="64"></a>