- Visibility6
- Citations8
- Sentiment100
- Site quality73
- AI readiness29
AI assistants rarely name Impinj in their answers, naming the company in 1 out of 60 answers. Its overall score is 38 points out of 100, which ranks it 605th of 2,047 companies measured. The Impinj website passes 4 of 14 technical checks for readiness with AI tools.
We asked 15 unbranded questions about the technology market: none named Impinj. AI assistants named it in 1 of 60 answers (1.7%). The typical technology company is named in 10.0% of answers. By how often it is named, Impinj ranks 211 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
“How to evaluate RAIN RFID platforms for large-scale supply chain automation?”
Evaluating RAIN RFID platforms for large-scale supply chain automation requires a comprehensive approach, considering various factors to ensure the chosen solution meets the specific needs and challenges of your organization. RAIN RFID offers significant advantages over traditional barcode systems, including automatic and high-accuracy bulk item identification, real-time visibility, and reduced manual labor.
Here's a breakdown of how to evaluate RAIN RFID platforms:
1. Understand Your Specific Needs and Use Cases:
Before evaluating platforms, clearly define your supply chain's unique req …
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 2: Bot-aware. Explicit AI bot rules and declared Content Signals.
- Markdown negotiation
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 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 rulesPartly met
Add explicit robots.txt groups for the main AI crawlers.
- study: 1.4%Content SignalsPassed
Content-Signal lines in robots.txt declaring search, AI input and AI training preferences.
- 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 35 of 100 · 97% of checks could run · checked on October 5, 2026 · www.impinj.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 8 AI crawlers by name. All others follow its general rules.
- GPTBot*blocked
- ClaudeBot*blocked
- Anthropic-AIallowed
- Google-Extended*blocked
- Applebot-Extended*blocked
- Meta-ExternalAgent*blocked
- FacebookBotallowed
- Bytespider*blocked
- CCBot*blocked
- Diffbotallowed
- Omgilibotallowed
- OAI-SearchBotallowed
- Claude-SearchBotallowed
- PerplexityBotallowed
- Applebotallowed
- Amazonbot*blocked
- YouBotallowed
- ChatGPT-Userallowed
- 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 US-listed.
- Why might a real-time item visibility solution fail to capture inventory accurately?
- How can RAIN RFID support intelligent store operations in retail environments?
- How does RAIN RFID compare to barcode systems for retail item tracking?
- What are the benefits of using RAIN RFID for real-time inventory tracking in supply chain operations?
- Best solutions for wirelessly connecting physical items to enterprise systems
- Physical intelligence platforms vs traditional IoT item tracking: what's the difference?
- Common issues when deploying RAIN RFID in warehouse environments and how to solve them
- Use cases for physical intelligence in fresh food supply chain management
- Best alternative technologies to physical intelligence platforms for tracking assets digitally
- Is adopting a physical intelligence platform for manufacturing worth the investment?
- Alternatives to RAIN RFID for real-time item-level visibility in logistics
- How to evaluate RAIN RFID platforms for large-scale supply chain automation?
- Typical costs involved in implementing RAIN RFID tracking for mid-sized enterprises
- What industries benefit most from real-time digital tracking of physical assets?
- Factors that influence pricing for physical intelligence solutions in manufacturing automation
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.