- Visibility19
- Citations4
- Sentiment50
- Site quality80
- AI readiness36
AI assistants name Waters in 18.3% of answers, which is more often than the typical company in its sector at 3.3%. Waters has an overall score of 34 out of 100, ranking 889th of 2,047 companies. Its website passes 5 of 14 technical checks for AI tool readiness.
We asked 15 unbranded questions about the healthcare market: none named Waters. AI assistants named it in 11 of 60 answers (18.3%). The typical healthcare company is named in 3.3% of answers. By how often it is named, Waters ranks 10 of 105 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.
105 companies in this sector. The line on each bar is the typical company.
An answer that names the company
“Best analytical instrument configurations for rapid PFAS analysis”
For rapid PFAS analysis, the best-performing configurations are typically UHPLC/LC-MS/MS with a triple quadrupole, or LC-HRMS (QTOF/Orbitrap) when you also need screening and confirmation of unknown PFAS.
The fastest practical setups in the results are:
UHPLC + triple quadrupole LC-MS/MS for targeted quantitation, because it offers high specificity, accuracy, and precision for routine PFAS measurement.
Short-gradient LC methods with PFAS-optimized columns, such as a method reporting 33 PFAS in 5 minutes on an Ascentis Express PFAS HPLC column. …
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. Waters 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
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 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 32 of 100 · 97% of checks could run · checked on October 3, 2026 · www.waters.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 6 AI crawlers by name. All others follow its general rules.
- GPTBotpartly
- ClaudeBotpartly
- Anthropic-AIpartly
- Google-Extended*allowed
- Applebot-Extendedpartly
- Meta-ExternalAgentpartly
- FacebookBotpartly
- Bytespiderpartly
- CCBotpartly
- Diffbotpartly
- Omgilibotpartly
- OAI-SearchBot*allowed
- Claude-SearchBot*allowed
- PerplexityBot*allowed
- Applebotpartly
- Amazonbotpartly
- YouBotpartly
- ChatGPT-User*allowed
- Claude-User*allowed
- 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 advanced LC-MS systems worth the investment for small academic labs?
- Best analytical instrument configurations for rapid PFAS analysis
- What causes baseline noise in mass spectrometry readings and how can it be reduced?
- Other analytical workflows suitable for DMPK studies if you don’t have LC-MS access?
- What is the typical price range for analytical laboratory software licenses in the US?
- How do mass spectrometry systems compare to gas chromatography for industrial analysis?
- What are the best analytical instruments for pharmaceutical research labs?
- Common issues with liquid chromatography calibration and how to fix them
- How much should a mid-sized lab budget for a new LC-MS setup, including installation?
- Which laboratory systems support GLP-1 drug development processes?
- What are some software options for managing chromatography data besides proprietary platforms?
- Alternatives to traditional HPLC for analyzing complex biological samples
- Which liquid chromatography systems are recommended for environmental testing?
- How to decide if you need integrated data analysis software for lab instruments?
- Differences between HPLC and UPLC for laboratory workflows
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/waters.com"><img src="https://aeo-audit.rezolve.com/us/badges/waters.com.svg" alt="Overall score 34 of 100, US AI Visibility Study 2026" width="280" height="64"></a>