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.
1,414 of 2,219
its rank by overall score
Closing balance

Named in

0of 60, its tower is dark

by 0 of 4 assistants

Statement note

What this means for StraitsX

AI assistants do not name StraitsX in any of their 60 answers, while the typical company in its sector is named in 1.7% of answers. Its overall score is 27 out of 100, ranking 1,414th of 2,219 companies. Its website passes 5 out of 14 technical checks for AI tool readiness.

We asked 15 unbranded questions about its market, so no question mentioned StraitsX by name. AI assistants named it in none of the 60 answers. Counting only how often it is named, it ranks 67th of 102 in its sector. The typical crypto and digital asset 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
27Overall score
  • Visibility0
  • Citations1
  • Sentiment50
  • Site quality80
  • AI readiness36
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
5/14
technical checks passed. Typical for its sector: 4
Rank in its sector
66 of 102
by overall score, where the typical crypto and digital asset company scores 30

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Line itemsSection 01

Every question, and where the company came up

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

  1. 01What should enterprises consider before using stablecoin rails for global payments?0/4
  2. 02Best options for card programs without using stablecoin rails0/4
  3. 03Alternatives to using stablecoins for cross-border business payments0/4
  4. 04Typical pricing structure for stablecoin-backed cross-border payment solutions in the US0/4
  5. 05How does stablecoin-backed card issuance compare to traditional prepaid card solutions?0/4
  6. 06Stablecoin payments infrastructure vs legacy settlement networks for cross-border transfers—what are the key differences?0/4
  7. 07Is stablecoin-powered card infrastructure worth integrating for financial institutions?0/4
  8. 08Use cases for stablecoin-backed card programs beyond remittances0/4
  9. 09Which regulated providers offer compliant stablecoin payment solutions for US-based fintechs?0/4
  10. 10What are the best stablecoin payment infrastructure providers for launching card programs in the US?0/4
  11. 11How can fintech companies enable cross-border payments with stablecoins?0/4
  12. 12What fees are associated with stablecoin payment infrastructure for global card issuance?0/4
  13. 13Why might stablecoin settlement for card programs fail to process?0/4
  14. 14How can enterprises use stablecoin-powered infrastructure for treasury management?0/4
  15. 15Common issues when integrating stablecoin wallets with card issuance platforms0/4
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 Claude actually said

The company is not named in this answer

Claudedid not name the company

“What should enterprises consider before using stablecoin rails for global payments?”

Based on current information, here are the key considerations enterprises should evaluate before using stablecoin rails for global payments:

Regulatory and Compliance Risk

Stablecoins can de-peg and lose value based on market conditions and issuer risks. Additionally, stablecoins rely on centralized issuers, and their stability depends on reserve quality, operational controls, and regulatory compliance.

An enterprise rail needs programmatic API access, multi-chain coverage, compliance and screening hooks (OFAC, KYB, travel rule), and operational guarantees the treasury team can defend in …

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
    Circle
    6
  2. 02
    Fireblocks
    5
  3. 03
    BVNK
    4
  4. 04
    Prime Trust
    1

Share of mentions

CompanyShare
  1. Circle
    35.0%
  2. BVNK
    30.0%
  3. Fireblocks
    25.0%
  4. Stably
    5.0%
  5. Prime Trust
    5.0%
  6. StraitsX
    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
    circle.com
    12
  2. 02
    bridge.xyz
    11
  3. 03
    bvnk.com
    8
  4. 04
    crossmint.com
    8
  5. 05
    lithic.com
    8
  6. 06
    visa.com
    8
  7. 07
    mckinsey.com
    8
  8. 08
    utila.io
    7
  9. 09
    fireblocks.com
    7
  10. 10
    stripe.com
    7

StraitsX is in the study as a digital asset 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 StraitsX 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
1

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 crypto and digital asset companies

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

Overall score
27
Ranks 66 of 102. Typical company: 30
Named in answers
0.0%
Ranks 67 of 102. Typical company: 1.7%
AI readiness
36
Ranks 21 of 102. Typical company: 33
Against its categorySection 08

Compared with digital asset infrastructure companies

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

Overall score
27
Ranks 51 of 80. Typical company: 29
Named in answers
0.0%
Ranks 51 of 80. Typical company: 1.7%
AI readiness
36
Ranks 16 of 80. Typical company: 36
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. StraitsX 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
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
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 35 of 100 · 97% of checks could run · checked on October 9, 2026 · www.straitsx.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

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%
  • 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%
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

  • GPTBotpartly
  • ClaudeBotpartly
  • Anthropic-AIpartly
  • Google-Extendedpartly
  • Applebot-Extendedpartly
  • Meta-ExternalAgentpartly
  • FacebookBotpartly
  • Bytespiderpartly
  • CCBotpartly
  • Diffbotpartly
  • Omgilibotpartly

AI search

  • OAI-SearchBotpartly
  • Claude-SearchBotpartly
  • PerplexityBotpartly
  • Applebotpartly
  • Amazonbotpartly
  • YouBotpartly

Answering questions

  • ChatGPT-Userpartly
  • Claude-Userpartly
  • Perplexity-Userpartly
  • DuckAssistBotpartly
  • MistralAI-Userpartly

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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