Of 60 answers

The most named companies in the study, and S&P 500 financials, with how many of their 60 AI answers named them.

Back to the study
AI visibility statementFinance AI Visibility Study 2026Issued October 14, 2026
Account holder
Statement period
October 9 to 14, 2026
when the AI assistants were asked
Account no.
1,189 of 2,219
its rank by overall score
Place in its category
93rd of 203 payment processors
Closing balance

Named in

0of 60, its tower is dark

by 0 of 4 assistants

Statement note

What this means for PayNearMe

AI assistants do not name PayNearMe in any of their 60 answers. Its overall score is 28 out of 100, compared with 27 for the typical company in its sector. PayNearMe's website passes 3 out of 14 technical checks for readiness for AI tools.

We asked 15 unbranded questions about its market, so no question mentioned PayNearMe by name. AI assistants named it in none of the 60 answers. Counting only how often it is named, it ranks 179th of 375 in its sector. The typical cards and payments company is named in 0.0% of answers.

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 peers.

Overall score
28Overall score
  • Visibility0
  • Citations4
  • Sentiment50
  • Site quality87
  • AI readiness21
Summary of account
Named by AI in
0.0%
0 of 60 answers
Share of mentions
0.0%
of the mentions of it and its 5 peers
AI readiness
3/14
technical checks passed. Typical for its sector: 4
Rank in its sector
156 of 375
by overall score, where the typical cards and payments company scores 27

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Line itemsSection 01

Every question, and where the company came up

PayNearMe came up on 0 of 15 questions. Open any window to read that answer.

  1. 01How can businesses increase self-service payment rates among customers?0/4
  2. 02What are the key features to look for in a business payments and bill processing platform?0/4
  3. 03Is investing in a modern payment processing platform worth it for reducing manual billing workload?0/4
  4. 04How much do automated bill payment solutions typically charge per transaction for businesses?0/4
  5. 05Traditional bank payment solutions vs. cloud-based bill processing systems—what are the main differences for businesses?0/4
  6. 06Which features help resolve payment exceptions faster in a business payment acceptance platform?0/4
  7. 07Alternatives to modern online bill payment platforms for businesses with high transaction volumes0/4
  8. 08Best payment acceptance solutions for streamlining bill payments in small businesses0/4
  9. 09What pricing models are available for business-oriented payment processing platforms in the US?0/4
  10. 10What are effective ways for companies to offer multiple payment options for bill collection?0/4
  11. 11Does using an automated bill payment solution lower the overall cost of payment acceptance for companies?0/4
  12. 12What are some low-cost options for companies needing to accept a wide variety of payment methods?0/4
  13. 13How do you handle failed transactions in a business bill payment platform?0/4
  14. 14What are common issues businesses face when integrating bill processing platforms with existing accounting systems?0/4
  15. 15How does an all-in-one digital payment platform compare to using separate tools for billing and payment processing?0/4
Total namedOpenAI: 0/15Claude: 0/15Perplexity: 0/15Gemini: 0/15All assistants: 0/60
named the companyanswered without naming itdid not answer

Columns, left to right: OpenAI, Claude, Perplexity, Gemini. Across the study, on 50% of the questions where a company is named, only one AI assistant names it.

Transaction detailSection 02

What Perplexity actually said

The company is not named in this answer

Perplexitydid not name the company

“Alternatives to modern online bill payment platforms for businesses with high transaction volumes”

For businesses processing high transaction volumes, the strongest alternatives depend on whether you primarily need AP automation, global payouts, customer collections, or payment infrastructure:

Tipalti — Best for high-volume global vendor or marketplace payouts. It supports international payment methods, tax-form collection, compliance workflows, and multi-currency payments across many countries.

HighRadius — Best for large enterprises seeking broader finance automation, including order-to-cash, collections, cash application, and ERP integrations. It is likely excessiv …

The AI’s answer as we received it, shortened and not checked for accuracy.

PayeesSection 03

Where the mentions went

The companies these answers named, and how the mentions were split between this company and its peers.

Share of mentions

CompanyShare
  1. BillTrust
    100.0%
  2. PayNearMe
    0.0%
  3. Paymentus
    0.0%
  4. InvoiceCloud
    0.0%
  5. Fiserv – Biller Solutions
    0.0%
  6. Repay
    0.0%
ReferrersSection 04

Websites the AI used as sources

How many times each website was listed as a source in these answers

  1. 01
    bill.com
    21
  2. 02
    stripe.com
    12
  3. 03
    home.paynearme.com
    10
  4. 04
    highradius.com
    8
  5. 05
    ramp.com
    7
  6. 06
    fitsmallbusiness.com
    6
  7. 07
    airwallex.com
    5
  8. 08
    billtrust.com
    5
  9. 09
    quickbooks.intuit.com
    4
  10. 10
    learn.g2.com
    4

PayNearMe is in the study as a payment processor.

By assistantSection 05

Which AI assistants named the company

Answers naming it, out of answers received

Claude
0/15
Gemini
0/15
OpenAI
0/15
Perplexity
0/15
Market comparisonSection 06

How PayNearMe compares with all 2,219 companies

Every tower is a company in the study, taller for a higher overall score and lit where AI assistants named it. Its own group stays lit. Hover a tower to see it, and click to open it.

What makes up the score

Each part is scored out of 100.

Visibility
0

How often AI assistants name the company, and how that compares with its peers

Citations
4

How often AI uses the company's own website as a source

Sentiment
50

How positively AI describes the company

Site quality
87

How well built the website's own pages are

AI readiness
21

How easily AI tools can read and use the website

Visibility is calculated from the answers on this page. How the score is built.

Against its sectorSection 07

Compared with cards and payments companies

375 companies in this sector. The gold tick on each bar is the typical company.

Overall score
28
Ranks 156 of 375. Typical company: 27
Named in answers
0.0%
Ranks 179 of 375. Typical company: 0.0%
AI readiness
21
Ranks 216 of 375. Typical company: 29
Against its categorySection 08

Compared with payment processors

203 companies in this category. The gold tick on each bar is the typical company.

Overall score
28
Ranks 80 of 203. Typical company: 27
Named in answers
0.0%
Ranks 91 of 203. Typical company: 0.0%
AI readiness
21
Ranks 113 of 203. Typical company: 29
AI agentsSection 09

Ready for AI agents

What this website publishes for an AI agent to read, use and pay through, on a scale of six levels.

  1. 0
  2. 1
  3. 2
  4. 3
  5. 4
  6. 5

Level 1: Basic web presence. Two of robots.txt, a sitemap and Link headers are in place.

To reach level 2:
  • Content Signals
Can an AI agent check out here?

Not by itself. PayNearMe publishes none of the agent payment protocols we look for. An agent would have to click through the website like a person.

Agent payment protocols
  • x402Not present
  • MPPNot present
  • AP2Not present
  • ACPNot present
  • UCPNot present
Interfaces for AI agents
  • MCP Server CardNot present
  • A2A Agent CardNot present
  • Agent SkillsNot present
  • API CatalogNot present
  • llms.txtNot present
  • WebMCPCould not check
Show every check, for your technical team
Discoverability
72 of 100
  • robots.txtPassed

    A valid robots.txt with crawl rules at the site root.

    study: 86.1%
  • SitemapPartly met

    Serve an XML sitemap and reference it from robots.txt.

    study: 87.9%
  • Link headersNot met

    Send Link headers such as rel="api-catalog" or rel="describedby" on the homepage.

    study: 1.5%
  • DNS for AI DiscoveryNot present

    Advertise agent endpoints with SVCB records under _agents.

    study: 4.3%
Content accessibility
0 of 100
  • Markdown negotiationNot met

    Return a markdown version when asked with Accept: text/markdown, for example at the CDN.

    study: 6.2%
  • llms.txtNot met

    Publish an llms.txt with a short summary and the key links.

    study: 31.0%
Bot access control
32 of 100
  • AI bot rulesPartly met

    Add explicit robots.txt groups for the main AI crawlers.

    study: 92.7%
  • Content SignalsNot met

    Add a Content-Signal line for search, ai-input and ai-train to robots.txt.

    study: 2.3%
  • Web Bot AuthNot present

    Only relevant if you run your own agents or crawlers: publish a signing key directory.

    study: 0.3%
APIs, auth and MCP
0 of 100
  • API CatalogNot met

    List public APIs in a linkset at /.well-known/api-catalog.

    study: 1.3%
  • OAuth discoveryNot met

    Publish OpenID Connect or OAuth server metadata under /.well-known.

    study: 6.3%
  • OAuth Protected ResourceNot met

    Serve protected resource metadata at /.well-known/oauth-protected-resource.

    study: 5.3%
  • 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: 0.8%
  • 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: 1.0%
  • WebMCPCould not check

    Register key actions such as search or cart as WebMCP tools.

    study: 0.0%
  • ARD manifestNot met

    Publish an ai-catalog.json listing every agent interface.

    study: 0.2%

Score 24 of 100 · 97% of checks could run · checked on October 9, 2026 · home.paynearme.com · 2,200 companies scanned

See how every company did, and how this was measured.

AI readinessSection 10

The checks behind the AI readiness score

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 checks

Discoverability

  • Passedrobots.txt publishedstudy: 85.1%
  • Not metXML sitemapstudy: 79.4%
  • PassedHTTP Link headers (RFC 8288)study: 42.5%

Content Accessibility

  • Not metMarkdown content negotiationstudy: 7.4%
  • Not metllms.txt publishedstudy: 28.1%
  • PassedToken budget (page weight)study: 97.3%

Bot Access Control

  • Not metExplicit AI bot rulesstudy: 11.5%

API / Auth / MCP

  • Not metAPI Catalog (.well-known/api-catalog)study: 1.1%
  • Not metOAuth Authorization Server discoverystudy: 5.2%
  • Not metOAuth Protected Resource discoverystudy: 4.6%
  • Not metMCP Server Cardstudy: 0.2%
  • Not metA2A Agent Cardstudy: 0.0%
  • Not metWebMCP toolsstudy: 0.3%
  • Not metAgent Skills declaredstudy: 0.1%
AI crawlersSection 11

What AI crawlers may read (robots.txt)

This website sets no rules for any AI crawler by name, like 86% of the websites whose rules we could read. Every AI crawler follows its general rules.

Training AI

  • GPTBotblocked
  • ClaudeBotblocked
  • Anthropic-AIblocked
  • Google-Extendedblocked
  • Applebot-Extendedblocked
  • Meta-ExternalAgentblocked
  • FacebookBotblocked
  • Bytespiderblocked
  • CCBotblocked
  • Diffbotblocked
  • Omgilibotblocked

AI search

  • OAI-SearchBotblocked
  • Claude-SearchBotblocked
  • PerplexityBotblocked
  • Applebotblocked
  • Amazonbotblocked
  • YouBotblocked

Answering questions

  • ChatGPT-Userblocked
  • Claude-Userblocked
  • Perplexity-Userblocked
  • DuckAssistBotblocked
  • MistralAI-Userblocked

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.

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