- Visibility12
- Citations3
- Sentiment63
- Site quality80
- AI readiness36
AI assistants name TE Connectivity in 5% of answers, which is half as often as the typical company in the technology sector. Its overall score is 34 out of 100, ranking 932nd of 2,047 companies. The company's website passes 5 out of 14 technical checks for AI tool readiness.
We asked 15 unbranded questions about the technology market: none named TE Connectivity. 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, TE Connectivity 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
“What are the most reliable connector types for harsh industrial environments?”
For harsh industrial environments, reliable connector types are essential to ensure uninterrupted power, signal, and data transmission despite challenging conditions like vibration, extreme temperatures, moisture, dust, and chemicals. Choosing the appropriate connector type is crucial for system reliability and to avoid costly field failures.
Here are some of the most reliable connector types for harsh industrial environments:
Circular Connectors (MIL-SPEC) These are considered the gold standard for reliability in extreme environments. They are built to military specifications (e.g., …
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.txtCould not check
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 AuthCould not check
Only relevant if you run your own agents or crawlers: publish a signing key directory.
- study: 0.3%API CatalogCould not check
List public APIs in a linkset at /.well-known/api-catalog.
- study: 11.8%OAuth discoveryCould not check
Publish OpenID Connect or OAuth server metadata under /.well-known.
- study: 10.3%OAuth Protected ResourceCould not check
Serve protected resource metadata at /.well-known/oauth-protected-resource.
- study: 0.0%auth.mdCould not check
Publish an auth.md describing how agents sign in.
- study: 0.2%MCP Server CardCould not check
Offer an MCP server and publish its server card under /.well-known.
- study: 0.1%A2A Agent CardCould not check
Publish an agent card at /.well-known/agent-card.json.
- study: 0.2%Agent SkillsCould not check
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 manifestCould not check
Publish an ai-catalog.json listing every agent interface.
Score 45 of 100 · 53% of checks could run · checked on October 5, 2026 · www.te.com · 2,047 companies scanned
5 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%
- PassedExplicit 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 rules for 4 AI crawlers by name. All others follow its general rules.
- GPTBot*partly
- ClaudeBotpartly
- Anthropic-AIpartly
- Google-Extendedpartly
- Applebot-Extendedpartly
- Meta-ExternalAgent*blocked
- FacebookBotpartly
- Bytespiderpartly
- CCBotpartly
- Diffbotpartly
- Omgilibotpartly
- OAI-SearchBotpartly
- Claude-SearchBotpartly
- PerplexityBotpartly
- Applebot*blocked
- Amazonbot*blocked
- 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.
- How to diagnose faulty industrial pressure sensors?
- Which connector types are best for robotics in manufacturing plants?
- How do board-to-board connectors compare to wire-to-board connectors in data communication systems?
- What are common causes of signal loss in high-speed connectors?
- What are the most reliable connector types for harsh industrial environments?
- How does sensor cost vary by accuracy and response time?
- Recommended sensors for predictive maintenance in industrial machinery
- Is it necessary to buy high-spec sensors for aerospace environments?
- Average price range for industrial-grade connectors in the US
- Most common certifications for electrical connectors used in the US
- What are some options besides thermocouple sensors for temperature monitoring?
- Alternatives to metal shell connectors for environments with high electromagnetic interference
- Are heavy-duty connectors worth the extra cost for factory automation projects?
- Difference between circular and rectangular connectors for industrial use
- Best sensors for monitoring temperature in automotive 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/te.com"><img src="https://aeo-audit.rezolve.com/us/badges/te.com.svg" alt="Overall score 34 of 100, US AI Visibility Study 2026" width="280" height="64"></a>