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.

SWIFT47/60TRANSUNION46/60EXPERIAN42/60COINSTAR41/60NAVY FEDERAL CREDIT UNION41/60ZELLE41/60BLOOMBERG L.P.38/60TRADINGVIEW38/60BANCO POPULAR DE PUERTO RICO37/60PAYPAL37/60VENMO37/60CHEXSYSTEMS33/60EQUIFAX33/60MORNINGSTAR32/60S&P GLOBAL31/60ALPACA MARKETS30/60COINBASE30/60PINWHEEL29/60STRIPE29/60XERO29/60ACORNS28/60AFFIRM28/60PAYFAST (PAYGATE)28/60PAYONEER28/60INTERACTIVE BROKERS26/60CHARLES SCHWAB19/60THE HARTFORD9/60MOODY'S21/60CME GROUP19/60ACCENTURE11/60CHUBB10/60MORGAN STANLEY6/60AMERICAN EXPRESS14/60SYNCHRONY FINANCIAL12/60FACTSET20/60NASDAQ19/60ALLSTATE11/60WELLS FARGO18/60PAYCHEX10/60ARES MANAGEMENT3/60
Rezolve Ai
MethodDemo
Back to the study
AI visibility statementFinance AI Visibility Study 2026Issued October 14, 2026
Account holder

Moon Technologies

themooncard.com

Banking and fintech infrastructureFinancial technology and data

Money20/20 attendee

Statement period
October 9 to 14, 2026
when the AI assistants were asked
Account no.
2,163 of 2,219
its rank by overall score
Place in its category
308th of 315 fintech infrastructure companies
Closing balance

Named in

0of 60, its tower is dark

by 0 of 4 assistants

Statement note

What this means for Moon Technologies

AI assistants do not name this fintech infrastructure company in any of their 60 answers to market questions. Its overall score is 21 out of 100, placing it 2,163rd of 2,219 companies in the study. The company's website passes 1 of 14 technical checks for readiness for AI tools.

We asked 15 unbranded questions about its market, so no question mentioned Moon Technologies by name. AI assistants named it in none of the 60 answers. Counting only how often it is named, it ranks 334th of 574 in its sector. The typical financial technology and data company is named in 1.7% 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
21Overall score
  • Visibility0
  • Citations0
  • Sentiment50
  • Site quality60
  • AI readiness7
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
1/14
technical checks passed. Typical for its sector: 4
Rank in its sector
562 of 574
by overall score, where the typical financial technology and data company scores 29

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Line itemsSection 01

Every question, and where the company came up

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

  1. 01Options besides API-based providers for powering embedded payment features?0/4
  2. 02How can financial service providers address security issues in payment software integration?0/4
  3. 03Examples of how businesses use card enablement technology to launch branded payment products?0/4
  4. 04Alternatives to card-focused payment enablement platforms for delivering digital payments?0/4
  5. 05What affects monthly fees for enterprise digital payment solutions providers?0/4
  6. 06Is it worth investing in integrated card and payment enablement technology for fintech startups?0/4
  7. 07How do card issuing platforms differ from digital wallet enablement solutions?0/4
  8. 08What should enterprises look for when choosing digital payment infrastructure providers?0/4
  9. 09Typical cost structures for API-based card and payment enablement technology in the US?0/4
  10. 10Key differences between full-stack payment processing technology and API-driven payment enablers?0/4
  11. 11Why do card transactions sometimes fail with payment enablement platforms?0/4
  12. 12What are the best card and digital payment enablement solutions for financial institutions in the US?0/4
  13. 13Best practices for integrating digital payment solutions into existing banking systems?0/4
  14. 14What are common features of secure payment enablement platforms for consumer fintech apps?0/4
  15. 15Which payment technology platforms are popular for launching digital card programs for enterprises?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 card-focused payment enablement platforms for delivering digital payments?”

Alternatives to card-focused payment-enablement platforms generally fall into five categories:

Account-to-account and open-banking payments: Providers such as Plaid, Trustly, and GoCardless enable bank-account payments, ACH, direct debit, and pay-by-bank flows—often reducing card fees and supporting recurring payments.

Digital wallets and mobile payments: PayPal, Apple Pay, Google Pay, Alipay, WeChat Pay, and Cash App Pay can provide wallet-based checkout and stored-value experiences. Platforms such as SnapPay support several regional wallets alongside cards.[1 …

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.

Named instead

CompanyTimes named
  1. 01
    Marqeta
    9
  2. 02
    Unit
    3
  3. 03
    Bond
    2
  4. 04
    Synapse
    2
  5. 05
    Galileo Financial Technologies
    2

Share of mentions

CompanyShare
  1. Marqeta
    38.5%
  2. Galileo Financial Technologies
    34.6%
  3. Unit
    15.4%
  4. Synapse
    7.7%
  5. Bond
    3.8%
  6. Moon Technologies
    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
    stripe.com
    20
  2. 02
    connectpay.com
    9
  3. 03
    airwallex.com
    6
  4. 04
    fiserv.com
    6
  5. 05
    enfuce.com
    6
  6. 06
    marqeta.com
    6
  7. 07
    dashdevs.com
    5
  8. 08
    bamboodt.com
    5
  9. 09
    sourceforge.net
    5
  10. 10
    fisglobal.com
    4

Moon Technologies is in the study as a fintech infrastructure company.

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 Moon Technologies 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
0

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

Sentiment
50

How positively AI describes the company

Site quality
60

How well built the website's own pages are

AI readiness
7

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 financial technology and data companies

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

Overall score
21
Ranks 562 of 574. Typical company: 29
Named in answers
0.0%
Ranks 334 of 574. Typical company: 1.7%
AI readiness
7
Ranks 533 of 574. Typical company: 29
Against its categorySection 08

Compared with fintech infrastructure companies

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

Overall score
21
Ranks 308 of 315. Typical company: 28
Named in answers
0.0%
Ranks 168 of 315. Typical company: 1.7%
AI readiness
7
Ranks 293 of 315. 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.

This website turned most of our scan away, so it has no level. Only 5% of the checks could run. That reflects the website’s rules for automated visitors, and an AI agent arriving by itself meets the same rules.

Can an AI agent check out here?

We could not tell. The website turned away our requests for the files an agent would read. An agent arriving by itself is turned away the same way.

Agent payment protocols
  • x402Not present
  • MPPCould not check
  • AP2Not present
  • ACPCould not check
  • UCPCould not check
Interfaces for AI agents
  • MCP Server CardCould not check
  • A2A Agent CardCould not check
  • Agent SkillsCould not check
  • API CatalogCould not check
  • llms.txtCould not check
  • WebMCPCould not check
Show every check, for your technical team
Discoverability
0 of 100
  • robots.txtCould not check

    Publish a valid robots.txt with crawl rules and a Sitemap line.

    study: 86.1%
  • SitemapCould not check

    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
  • Markdown negotiationCould not check

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

    study: 6.2%
  • llms.txtCould not check

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

    study: 31.0%
Bot access control
  • AI bot rulesCould not check

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

    study: 92.7%
  • Content SignalsCould not check

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

    study: 2.3%
  • Web Bot AuthCould not check

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

    study: 0.3%
APIs, auth and MCP
  • API CatalogCould not check

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

    study: 1.3%
  • OAuth discoveryCould not check

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

    study: 6.3%
  • OAuth Protected ResourceCould not check

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

    study: 5.3%
  • auth.mdCould not check

    Publish an auth.md describing how agents sign in.

    study: 0.2%
  • MCP Server CardCould not check

    Offer an MCP server and publish its server card under /.well-known.

    study: 0.8%
  • A2A Agent CardCould not check

    Publish an agent card at /.well-known/agent-card.json.

    study: 0.2%
  • Agent SkillsCould not check

    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 manifestCould not check

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

    study: 0.2%

Score 0 of 100 · 5% of checks could run · checked on October 9, 2026 · themooncard.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

1 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

  • Not metrobots.txt publishedstudy: 85.1%
  • Not metXML sitemapstudy: 79.4%
  • Not metHTTP 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%
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End of statement
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