- Visibility7
- Citations1
- Sentiment50
- Site quality87
- AI readiness36
AI assistants rarely name Abbott Laboratories, mentioning it in 2 out of 60 answers. In the same answers, they also name Dexcom, Medtronic, and Boston Scientific. Its overall score is 31 out of 100, which ranks 1,158th of 2,047 companies. The website passes 3 of 14 technical checks for readiness for AI tools.
We asked 15 unbranded questions about the healthcare market: none named Abbott Laboratories. AI assistants named it in 2 of 60 answers (3.3%). The typical healthcare company is named in 3.3% of answers. By how often it is named, Abbott Laboratories ranks 48 of 105 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.
105 companies in this sector. The line on each bar is the typical company.
An answer that names the company
“How much do advanced cholesterol testing kits cost in the US?”
In the US, advanced cholesterol testing kits typically cost about $85 to $215 for consumer lab panels, while some home-use devices can run from about $49 up to $1,800 depending on how advanced they are.
A practical breakdown is:
Mail-in or lab-based advanced panels: about $85–$215. Quest Health lists a high-risk heart health panel with Lp(a) at $68 plus a $6 physician fee, and an advanced heart health panel with ApoB at $172 plus a $6 physician fee.
At-home cholesterol kits with broader markers: about $49–$99 for more consum …
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 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.mdNot met
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 37 of 100 · 65% of checks could run · checked on October 5, 2026 · www.abbott.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.
- Is investing in wearable heart monitors really worth it for patients with chronic heart conditions?
- Are smart nutrition tracking devices cost-effective for people looking to monitor their diet?
- What is the price range for medical nutrition supplements through insurance?
- How much do advanced cholesterol testing kits cost in the US?
- Non-invasive alternatives to traditional cardiovascular monitoring methods
- Alternatives to implantable pain management systems for chronic pain relief
- Common problems with rechargeable medical devices for pain management and how to fix them
- Why might a continuous glucose monitor suddenly stop sending data to my app?
- Best medical device features for elderly patients needing daily cardiovascular support
- Top at-home diagnostic testing solutions for families in the US
- What are the best medical devices for managing cardiovascular health in adults?
- How do remote monitoring tools support diabetes management for busy adults?
- What are other options if rapid diagnostic testing is not covered by insurance?
- How do continuous glucose monitoring systems compare to traditional fingerstick methods?
- Diagnostic blood tests vs. point-of-care analyzers for routine health screenings
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.