- Visibility13
- Citations0
- Sentiment50
- Site quality80
- AI readiness36
AI assistants name VeriFone in 6.7% of answers, compared with 10% for the typical company in its sector. Its overall score is 31 out of 100, ranking 1,141st of 2,047 companies. The VeriFone website passes 5 of 14 technical checks of how ready it is for AI tools.
We asked 15 unbranded questions about the technology market: none named VeriFone. AI assistants named it in 4 of 60 answers (6.7%). The typical technology company is named in 10.0% of answers. By how often it is named, VeriFone ranks 165 of 273 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.
273 companies in this sector. The line on each bar is the typical company.
An answer that names the company
“Leading options for unified payment solutions with both hardware and software support?”
Unified payment solutions aim to streamline all transaction types—online, in-person, and mobile—through a single infrastructure, simplifying operations and data management for businesses. These platforms often provide both the software and hardware necessary to achieve this integration.
Here are some leading options for unified payment solutions with both hardware and software support:
1. Stripe:
Stripe is a widely recognized platform for unified global payment acceptance, known for its developer-friendly API and comprehensive suite of tools.
Software: Stripe offers robust APIs …
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 · www.verifone.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 US-listed.
- Best options for accepting mobile and contactless payments without installing traditional payment hardware?
- What alternatives exist to dedicated payment terminals for merchants?
- Leading options for unified payment solutions with both hardware and software support?
- What are the typical costs associated with integrated payment processing platforms in the US?
- POS terminals with built-in payment processing versus separate payment gateways—what are the pros and cons?
- Cloud-based payment processing vs on-premise payment solutions for retailers?
- What are the best integrated payment processing platforms for mid-sized US businesses?
- How reliable are unified payment systems for high transaction volumes in the United States?
- What are some flexible payment platforms that support international and cross-border sales?
- How do transaction fees differ between hardware-based payment terminals and purely digital platforms?
- How can payment platforms help streamline in-store and online transactions?
- Why might a payment terminal fail to connect with backend processing systems?
- What type of payment processing setup suits multi-location retail businesses?
- Common issues when integrating payment solutions with ecommerce platforms?
- Is investing in an all-in-one payment platform worth it for expanding businesses?
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/verifone.com"><img src="https://aeo-audit.rezolve.com/us/badges/verifone.com.svg" alt="Overall score 31 of 100, US AI Visibility Study 2026" width="280" height="64"></a>