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.
1,073 of 2,219
its rank by overall score
Place in its category
84th of 203 payment processors
Closing balance

Named in

1of 60 answers

by 1 of 4 assistants

Statement note

What this means for Pebl

AI assistants rarely name this payment processor, mentioning it in 1 of 60 answers, alongside companies like Square and PayPal Zettle. Its overall score is 28 out of 100, which ranks it 1,073rd of 2,219 companies. The website passes 5 of 14 technical checks for readiness with AI tools.

We asked 15 unbranded questions about its market, so no question mentioned Pebl by name. AI assistants named it in 1 of the 60 answers. Counting only how often it is named, it ranks 133rd 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
  • Visibility2
  • Citations0
  • Sentiment50
  • Site quality80
  • AI readiness36
Summary of account
Named by AI in
1.7%
1 of 60 answers
Share of mentions
1.8%
of the mentions of it and its 5 peers
AI readiness
5/14
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

Pebl came up on 1 of 15 questions. Open any window to read that answer.

  1. 01How does accepting payments via SMS compare to using invoicing for service providers?0/4
  2. 02Are there any hidden fees to watch for with phone-based payment solutions for small business owners?0/4
  3. 03Why might a contactless payment not go through on a mobile payment acceptance app?0/4
  4. 04Mobile payment acceptance vs traditional card readers — which is better for retailers looking to cut hardware costs?0/4
  5. 05How can small businesses use their smartphones to accept tap-to-pay and QR code payments without extra hardware?0/4
  6. 06What are some common ways service providers can use invoicing features in mobile payment solutions?0/4
  7. 07Is using a phone-based payment acceptance platform worth it for a small trade business?0/4
  8. 08What are the best mobile payment platforms for teams that need to accept payments on the go?0/4
  9. 09How much do mobile payment acceptance apps typically charge per transaction in the US?0/4
  10. 10How can retailers use QR codes to speed up in-person sales transactions?0/4
  11. 11Can freelancers accept payments without a physical card reader, and if so, what options are available?0/4
  12. 12Which mobile EFTPOS solutions offer fast setup for small team environments?1/4
  13. 13What should I look for in a payment acceptance solution when I have a mobile retail team?0/4
  14. 14How do you handle a failed payment link transaction in a payment app for small businesses?0/4
  15. 15What are some alternatives to using hardware terminals for accepting card payments?0/4
Total namedOpenAI: 0/15Claude: 0/15Perplexity: 0/15Gemini: 1/15All assistants: 1/60
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 Gemini actually said

An answer that names the company

Gemininamed the company

“Which mobile EFTPOS solutions offer fast setup for small team environments?”

Several mobile EFTPOS solutions offer fast setup and are suitable for small team environments, often by turning existing smartphones into payment terminals or providing portable dedicated devices.

Solutions leveraging existing smartphones (Tap to Pay): These are generally the quickest to set up and ideal for teams as multiple users can utilize their own devices.

Pebl Tap to Pay on iPhone: Allows team members to use their iPhones (iPhone XS or later) to accept payments with no extra hardware. Setup involves downloading the app, providing business information, and adding team membe …

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.

Also named

CompanyTimes named
  1. 01
    Square
    18
  2. 02
    PayPal Zettle
    5
  3. 03
    SumUp
    4
  4. 04
    Helcim
    4
  5. 05
    Stripe Terminal
    4

Share of mentions

CompanyShare
  1. Square
    33.9%
  2. Stripe Terminal
    33.9%
  3. PayPal Zettle
    14.3%
  4. Helcim
    10.7%
  5. SumUp
    5.4%
  6. Pebl
    1.8%
ReferrersSection 04

Websites the AI used as sources

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

  1. 01
    jim.com
    17
  2. 02
    stripe.com
    14
  3. 03
    fitsmallbusiness.com
    7
  4. 04
    squareup.com
    6
  5. 05
    paypal.com
    5
  6. 06
    kurvpay.com
    5
  7. 07
    nerdwallet.com
    5
  8. 08
    tyro.com
    5
  9. 09
    theretailexec.com
    5
  10. 10
    uschamber.com
    4

Pebl is in the study as a payment processor.

By assistantSection 05

Which AI assistants named the company

Answers naming it, out of answers received

Gemini
1/15
Claude
0/15
OpenAI
0/15
Perplexity
0/15
Market comparisonSection 06

How Pebl 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
2

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

Citations
0

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

Sentiment
50

How positively AI describes the company

Site quality
80

How well built the website's own pages are

AI readiness
36

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
1.7%
Ranks 133 of 375. Typical company: 0.0%
AI readiness
36
Ranks 41 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
1.7%
Ranks 64 of 203. Typical company: 0.0%
AI readiness
36
Ranks 23 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. Pebl 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
77 of 100
  • robots.txtPassed

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

    study: 86.1%
  • SitemapPassed

    An XML sitemap listing the pages, ideally referenced 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
63 of 100
  • AI bot rulesPassed

    Explicit robots.txt rules for AI crawlers such as GPTBot, ClaudeBot and PerplexityBot.

    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 32 of 100 · 97% of checks could run · checked on October 9, 2026 · www.peblpay.com.au · 2,200 companies scanned

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

AI readinessSection 10

The checks behind the AI readiness score

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 checks

Discoverability

  • Passedrobots.txt publishedstudy: 85.1%
  • PassedXML 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

  • PassedExplicit 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 rules for 21 AI crawlers by name. All others follow its general rules.

Training AI

  • GPTBot*allowed
  • ClaudeBot*allowed
  • Anthropic-AI*allowed
  • Google-Extended*allowed
  • Applebot-Extended*allowed
  • Meta-ExternalAgent*allowed
  • FacebookBot*allowed
  • Bytespider*allowed
  • CCBot*allowed
  • Diffbot*allowed
  • Omgilibot*allowed

AI search

  • OAI-SearchBot*allowed
  • Claude-SearchBot*allowed
  • PerplexityBot*allowed
  • Applebot*allowed
  • Amazonbot*allowed
  • YouBot*allowed

Answering questions

  • ChatGPT-User*allowed
  • Claude-User*allowed
  • Perplexity-Userallowed
  • DuckAssistBot*allowed
  • MistralAI-User*allowed

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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