- Visibility8
- Citations1
- Sentiment83
- Site quality73
- AI readiness21
AI assistants name MaxLinear in 5% of answers, which is less often than the typical company in the technology sector at 10%. Its overall score is 33 out of 100, ranking 999th of 2,047 companies. The website passes 3 of 14 technical checks for how ready it is for AI tools.
We asked 15 unbranded questions about the technology market: none named MaxLinear. AI assistants named it in 3 of 60 answers (5.0%). The typical technology company is named in 10.0% of answers. By how often it is named, MaxLinear ranks 185 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 investing in 224G DSP technology for retimers worth it for data centers?”
Investing in 224G DSP (Digital Signal Processing) technology for retimers is generally considered a worthwhile endeavor for data centers, particularly given the escalating demands of AI and high-performance computing (HPC) workloads. Here's a breakdown of why:
1. Enabling Higher Speeds and Bandwidth:
Foundation for 1.6Tbps: 224G SERDES (Serializer/Deserializer) is the core technology for next-generation 1.6Tbps links, which are becoming essential for hyperscale data centers, AI, and HPC applications.
Doubling Data Rates: 224G PAM4 (Pulse Amplitude Modulation 4-level) si …
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%SitemapPartly 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 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 23 of 100 · 100% of checks could run · checked on October 3, 2026 · www.maxlinear.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.
- 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 US-listed.
- Typical applications for 200G TIA semiconductors in data center environments
- How are AI-powered semiconductor platforms used in managing large-scale cloud infrastructure?
- Is investing in 224G DSP technology for retimers worth it for data centers?
- What is the price range for advanced connectivity chipsets used in US-based telecom networks?
- Top chipsets for AI-enabled 5G backhaul in telecom applications
- Are cloud-managed semiconductor platforms a good choice for modern industrial applications?
- How do storage accelerators compare to traditional SSD controllers for enterprise infrastructure?
- Why might an industrial connectivity solution experience intermittent data transmission errors?
- How much does it cost to upgrade data center infrastructure with industrial-grade network ICs?
- What are the best semiconductor solutions for scaling up data center connectivity?
- DSP vs FPGA for high-speed data center optics—what are the pros and cons?
- Common issues when deploying semiconductors for 5G backhaul and how to address them
- Best non-semiconductor solutions for boosting network reliability in data centers
- Alternatives to AI-enabled infrastructure semiconductors for smart buildings
- What are substitute technologies for high-speed data connectivity in large-scale industrial applications?
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/maxlinear.com"><img src="https://aeo-audit.rezolve.com/us/badges/maxlinear.com.svg" alt="Overall score 33 of 100, US AI Visibility Study 2026" width="280" height="64"></a>