- Visibility8
- Citations0
- Sentiment50
- Site quality80
- AI readiness36
AI assistants rarely name IDEX, with the company appearing in 1 of 60 answers, which is less often than the typical company in its sector. IDEX's overall score is 30 out of 100, ranking 1,255th of 2,047 companies measured. Its website passes 5 out of 14 technical checks for AI tool readiness.
We asked 15 unbranded questions about the industrial market: none named IDEX. AI assistants named it in 1 of 60 answers (1.7%). The typical industrial company is named in 5.0% of answers. By how often it is named, IDEX ranks 159 of 246 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.
246 companies in this sector. The line on each bar is the typical company.
An answer that names the company
“Average cost ranges for precision fluidics products in the US industrial market”
I'll search for information about precision fluidics product costs in the US industrial market.Let me search for more specific pricing information for precision fluidics products.Let me search for more specific cost/pricing data for precision fluidics components.Based on my research, I found limited specific pricing data readily available for individual precision fluidics products in the US industrial market. However, I can provide you with the following insights:
Market Size Context
The precision fluidics market size was valued at US$ 1,983.8 million in 2025 and is expected to reach US$ …
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 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 5, 2026 · idexcorp.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 8 AI crawlers by name. All others follow its general rules.
- GPTBot*allowed
- ClaudeBot*allowed
- Anthropic-AI*allowed
- Google-Extended*allowed
- Applebot-Extendedallowed
- Meta-ExternalAgentallowed
- FacebookBotallowed
- Bytespiderallowed
- CCBotallowed
- Diffbotallowed
- Omgilibotallowed
- OAI-SearchBot*allowed
- Claude-SearchBotallowed
- PerplexityBot*allowed
- Applebot*allowed
- Amazonbotallowed
- YouBotallowed
- ChatGPT-User*allowed
- 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 S&P 500.
- What are alternative options for precision dosing in water treatment facilities?
- How do engineered fluidics products differ from standard industrial pumps?
- Average cost ranges for precision fluidics products in the US industrial market
- Best alternatives to mechanical flow monitoring systems in fire & safety applications
- What are the best precision fluidics solutions for scientific laboratories?
- How are engineered fluid control products used in energy sector projects?
- Best use cases for mission-critical solutions in municipal water infrastructure
- What factors affect the pricing of custom-engineered solutions for scientific applications?
- Common problems with precision metering pumps in life sciences applications
- Which engineered systems are most reliable for municipal water treatment plants?
- What to do if an engineered fluidics system is losing calibration in a laboratory?
- Is it better to choose custom-designed industrial solutions or off-the-shelf fluidics systems?
- Alternatives to traditional industrial pumps for handling hazardous fluids
- Are high-end engineered fluidics systems worth the investment for fire safety applications?
- Mission-critical water handling vs energy industry fluidics: what are the key differences?
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.