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

N3XT

n3xt.io

Digital banks and neobanksBanking

Money20/20 attendee

Statement period
October 9 to 14, 2026
when the AI assistants were asked
Account no.
966 of 2,219
its rank by overall score
Place in its category
11th of 32 digital banks
Closing balance

Named in

1of 60 answers

by 1 of 4 assistants

Statement note

What this means for N3XT

AI assistants rarely name this digital bank, mentioning it in 1 of 60 answers. Its overall score is 29 out of 100, ranking 966th of 2,219 companies. The website passes 4 out of 14 technical checks, which reflects its technical readiness for AI tools.

We asked 15 unbranded questions about its market, so no question mentioned N3XT by name. AI assistants named it in 1 of the 60 answers. Counting only how often it is named, it ranks 156th of 394 in its sector. The typical banking 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
29Overall score
  • Visibility8
  • Citations0
  • Sentiment50
  • Site quality80
  • AI readiness29
Summary of account
Named by AI in
1.7%
1 of 60 answers
Share of mentions
100.0%
of the mentions of it and its 5 peers
AI readiness
4/14
technical checks passed. Typical for its sector: 3
Rank in its sector
143 of 394
by overall score, where the typical banking company scores 28

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Line itemsSection 01

Every question, and where the company came up

N3XT came up on 1 of 15 questions. Open any window to read that answer.

  1. 01How can manufacturers benefit from programmable, instant USD settlements in supply chain payments?0/4
  2. 02Why might a business experience delays with real-time USD settlement services?0/4
  3. 03Instant USD payment networks vs. wire transfers for B2B settlements—what are the key differences?0/4
  4. 04What are the best instant USD payment networks for businesses needing real-time settlements?0/4
  5. 05What features should US businesses look for in a secure instant USD payment platform?0/4
  6. 06What can cause issues with accessing 24/7 liquidity on an instant USD payment network?0/4
  7. 07Does adopting a full-reserve USD payment network improve cash flow reliability for B2B transactions?0/4
  8. 08How do full-reserve USD payment networks differ from traditional ACH systems for business payments?0/4
  9. 09What are alternatives for B2B firms seeking fast USD settlements outside of traditional banking hours?0/4
  10. 10How can B2B companies access 24/7 USD liquidity for large transactions?1/4
  11. 11Are there minimum balance requirements for accessing full-reserve USD payment services?0/4
  12. 12Is a programmable real-time settlement solution worth it for midsize businesses?0/4
  13. 13What are common ways that financial service providers use instant USD payment networks for their clients?0/4
  14. 14Which payment network types allow for real-time B2B USD transfers other than full-reserve systems?0/4
  15. 15How are transaction fees typically structured on B2B instant USD payment networks?0/4
Total namedOpenAI: 0/15Claude: 0/15Perplexity: 1/15Gemini: 0/15All 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 Perplexity actually said

An answer that names the company

Perplexitynamed the company

“How can B2B companies access 24/7 USD liquidity for large transactions?”

… Bank-managed instant USD networks: Providers such as N3XT offer programmable, always-on USD transfers within a regulated banking environment, with liquidity backed by cash and liquid government securities.

Institutional stablecoins: Companies can convert fiat into regulated dollar-denominated stablecoins such as USDC or USDT, transfer them on-chain at any time, and redeem them through an institutional off-ramp. This is particularly useful for cross-border settlement, though the fiat leg may still depend on provider cutoffs, compliance checks, and banking availability. …

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. N3XT
    100.0%
  2. TassatPay
    0.0%
  3. SigNet (Signature Bank)
    0.0%
  4. Silvergate Exchange Network (SEN)
    0.0%
  5. JP Morgan Coin Systems (Onyx)
    0.0%
  6. RTGS.global
    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
    10
  2. 02
    airwallex.com
    8
  3. 03
    xtransfer.com
    7
  4. 04
    eco.com
    7
  5. 05
    fasterpaymentscouncil.org
    6
  6. 06
    wise.com
    5
  7. 07
    f6s.com
    5
  8. 08
    ramp.com
    4
  9. 09
    usedots.com
    4
  10. 10
    photonpay.com
    4

N3XT is in the study as a digital bank.

By assistantSection 05

Which AI assistants named the company

Answers naming it, out of answers received

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

How N3XT 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
8

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
29

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 banking companies

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

Overall score
29
Ranks 143 of 394. Typical company: 28
Named in answers
1.7%
Ranks 156 of 394. Typical company: 0.0%
AI readiness
29
Ranks 82 of 394. Typical company: 29
Against its categorySection 08

Compared with digital banks

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

Overall score
29
Ranks 10 of 32. Typical company: 28
Named in answers
1.7%
Ranks 11 of 32. Typical company: 0.0%
AI readiness
29
Ranks 10 of 32. 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 0: Not yet agent-ready. Agents struggle to find basic information about the site.

To reach level 1:
  • 2 of robots.txt, Sitemap, Link headers
Can an AI agent check out here?

Not by itself. N3XT 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.txtPublished
  • WebMCPCould not check
Show every check, for your technical team
Discoverability
31 of 100
  • robots.txtNot met

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

    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
50 of 100
  • Markdown negotiationNot met

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

    study: 6.2%
  • llms.txtPassed

    An llms.txt that tells language models what the site offers.

    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 25 of 100 · 97% of checks could run · checked on October 9, 2026 · n3xt.io · 2,200 companies scanned

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

AI readinessSection 10

The checks behind the AI readiness score

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 checks

Discoverability

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

Content Accessibility

  • Not metMarkdown content negotiationstudy: 7.4%
  • Passedllms.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
All 2,219 companiesHow we measured this
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