- Visibility9
- Citations0
- Sentiment75
- Site quality67
- AI readiness29
AI assistants rarely name Celestica, mentioning it in only 2 of 60 answers. Its overall score is 31 out of 100, ranking 1,163rd of 2,047 companies. The website passes 4 of 14 technical checks for readiness with AI tools.
We asked 15 unbranded questions about the technology market: none named Celestica. AI assistants named it in 2 of 60 answers (3.3%). The typical technology company is named in 10.0% of answers. By how often it is named, Celestica ranks 200 of 273 in its sector.
Named fewer than three times in total. Read this as a sign that AI assistants rarely bring this company up, not as an exact comparison with its rivals.
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 top technology manufacturing and engineering service providers for high-growth industries?”
For technology manufacturing and engineering service providers in high-growth industries, the strongest names in the results are Siemens, ABB, Schneider Electric/AVEVA, Honeywell, Emerson, Rockwell Automation, PTC, TSMC, ASML, Foxconn, Sanmina, Celestica, and Fabrinet.
The best way to group them is by what they do:
Industrial automation / smart manufacturing platforms: Siemens, ABB, Emerson, Schneider Electric/AVEVA, and Honeywell are consistently ranked among the top vendors in smart manufacturing and digital transformation in manufacturing.[9 …
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 DiscoveryPassed
SVCB or HTTPS records under _agents that advertise agent endpoints.
- 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 rulesPassed
Explicit robots.txt rules for AI crawlers such as GPTBot, ClaudeBot and PerplexityBot.
- 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 33 of 100 · 97% of checks could run · checked on October 5, 2026 · www.celestica.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%
- 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%
- 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 5 AI crawlers by name. All others follow its general rules.
- GPTBot*blocked
- ClaudeBot*blocked
- Anthropic-AIpartly
- Google-Extendedpartly
- Applebot-Extendedpartly
- Meta-ExternalAgent*blocked
- FacebookBotpartly
- Bytespider*blocked
- CCBot*blocked
- 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.
- Price ranges for integrated technology platform solutions in the United States?
- What drives the cost of advanced design and manufacturing services for tech infrastructure companies?
- Who are leading providers of innovative platform solutions for connected technology ecosystems?
- Alternatives to traditional electronics manufacturing services for technology-focused businesses?
- What other service models exist besides turnkey engineering and manufacturing for technology organizations?
- Is it better to partner with a global design and engineering firm or work with multiple specialized vendors?
- What are the top technology manufacturing and engineering service providers for high-growth industries?
- How does design and engineering outsourcing differ from in-house solutions for tech infrastructure?
- Technology manufacturing services vs. contract electronics manufacturing—what's the difference?
- Examples of how lifecycle management services benefit businesses in emerging technologies?
- What should I do if my technology manufacturing partner misses production deadlines?
- Best advanced infrastructure solutions for businesses needing scalable technology platforms?
- Are end-to-end lifecycle solutions in technology manufacturing worth the investment for mid-sized businesses?
- Common manufacturing challenges in technology infrastructure projects and how to solve them?
- How can advanced engineering services support rapid product innovation in high-growth sectors?
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.