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

Named in

10of 60 answers

by 4 of 4 assistants

Statement note

What this means for SQRIL

AI assistants name this cross-border payments provider in 16.7% of answers, much more often than the typical company in its sector, which is named in 0%. Its overall score is 46 out of 100, ranking 40th of 2,219 companies and 5th of 375 in its sector. Its website passes 3 of 14 technical checks for AI tool readiness.

We asked 15 unbranded questions about its market, so no question mentioned SQRIL by name. AI assistants named it in 10 of the 60 answers. Counting only how often it is named, it ranks 49th of 375 in its sector. The typical cards and payments company is named in 0.0% of answers.

Overall score
46Overall score
  • Visibility35
  • Citations0
  • Sentiment92
  • Site quality87
  • AI readiness21
Summary of account
Named by AI in
16.7%
10 of 60 answers
Share of mentions
90.9%
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
5 of 375
by overall score, where the typical cards and payments company scores 27

Get the full report on SQRIL as a PDF

Enter your work email to download it.

We’ll use your email to follow up about this report. Privacy policy

Line itemsSection 01

Every question, and where the company came up

SQRIL came up on 4 of 15 questions. Open any window to read that answer.

  1. 01QR code payment rails versus mobile money solutions for emerging market remittances—what are the pros and cons?0/4
  2. 02Which methods besides scan-and-pay QR codes can fintech developers use for local disbursements in Africa and Asia?0/4
  3. 03What are common integration issues with stablecoin-powered QR code payments APIs for global fintech platforms?0/4
  4. 04Are there setup or monthly costs involved with using scan-to-pay APIs that enable local QR code payments overseas?0/4
  5. 05Which QR code payment solutions can help fintechs enable local currency payments in Asia, Africa, or Latin America?3/4
  6. 06Is it worth integrating a stablecoin-based QR code API for enabling payouts to local wallets in emerging markets?0/4
  7. 07How can developers resolve local currency settlement delays when using cross-border QR code payment APIs?0/4
  8. 08What are the best QR code payments APIs with stablecoin support for cross-border transactions in emerging markets?4/4
  9. 09What do typical transaction fees look like for QR code payments APIs with stablecoin support serving emerging market corridors?0/4
  10. 10How does a QR code payments API with stablecoin integration compare to a traditional card-based API for cross-border payments?0/4
  11. 11What alternatives exist to QR code payment APIs for enabling stablecoin remittances to emerging market users?0/4
  12. 12What are typical use cases for stablecoin-backed QR payment APIs in supporting gig worker or freelancer payouts internationally?0/4
  13. 13Do APIs that support local QR payment schemes offer better transaction efficiency than legacy remittance solutions?0/4
  14. 14How can a US-based fintech use a QR code payments API to facilitate instant local payments in Latin America?2/4
  15. 15What are the main substitutes for a stablecoin-integrated QR code API for cross-border consumer payments?1/4
Total namedOpenAI: 1/15Claude: 3/15Perplexity: 2/15Gemini: 4/15All assistants: 10/60
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

“What are the main substitutes for a stablecoin-integrated QR code API for cross-border consumer payments?”

While stablecoin-integrated QR code APIs like SQRIL offer a novel approach to cross-border consumer payments by enabling instant stablecoin-to-fiat conversions at the point of sale [markets.businessinsider.com], several alternative solutions exist, each with its own advantages and integration methods:

1. Traditional Fiat-to-Crypto Onramps and Offramps: These services facilitate the conversion of fiat currency to stablecoins (onramp) and vice-versa (offramp), often through widgets or APIs. While they don't directly integrate with QR codes for point-of-sale transactions in the same way SQRI …

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
    TransFi
    1

Share of mentions

CompanyShare
  1. SQRIL
    90.9%
  2. TransFi
    9.1%
  3. Poko
    0.0%
  4. Onramper
    0.0%
  5. Fuse Network
    0.0%
  6. Ramp
    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
    dlocal.com
    12
  2. 02
    stripe.com
    11
  3. 03
    spark.money
    9
  4. 04
    opendue.com
    9
  5. 05
    globenewswire.com
    7
  6. 06
    crossmint.com
    7
  7. 07
    linkedin.com
    7
  8. 08
    knowledge.antom.com
    6
  9. 09
    gsma.com
    5
  10. 10
    hitpayapp.com
    5

SQRIL is in the study as a cross-border payments provider.

By assistantSection 05

Which AI assistants named the company

Answers naming it, out of answers received

Gemini
4/15
Claude
3/15
Perplexity
2/15
OpenAI
1/15
Market comparisonSection 06

How SQRIL 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
35

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
92

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
46
Ranks 5 of 375. Typical company: 27
Named in answers
16.7%
Ranks 49 of 375. Typical company: 0.0%
AI readiness
21
Ranks 216 of 375. Typical company: 29
Against its categorySection 08

Compared with cross-border payments providers

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

Overall score
46
Ranks 2 of 84. Typical company: 27
Named in answers
16.7%
Ranks 10 of 84. Typical company: 0.0%
AI readiness
21
Ranks 51 of 84. 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. SQRIL 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
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 · sqril.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

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%
  • PassedXML 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%
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

  • GPTBotallowed
  • ClaudeBotallowed
  • Anthropic-AIallowed
  • Google-Extendedallowed
  • Applebot-Extendedallowed
  • Meta-ExternalAgentallowed
  • FacebookBotallowed
  • Bytespiderallowed
  • CCBotallowed
  • Diffbotallowed
  • Omgilibotallowed

AI search

  • OAI-SearchBotallowed
  • Claude-SearchBotallowed
  • PerplexityBotallowed
  • Applebotallowed
  • Amazonbotallowed
  • YouBotallowed

Answering questions

  • ChatGPT-Userallowed
  • Claude-Userallowed
  • Perplexity-Userallowed
  • DuckAssistBotallowed
  • MistralAI-Userallowed

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.

Take it with you

Get the full report on SQRIL as a PDF

Every number on this page in a PDF you can keep and share with your team. Enter your work email to download it.

We’ll use your email to follow up about this report. Privacy policy

ShareSection 12

Share this result

Overall score 46 of 100 badge for SQRIL

A badge of this result that you can show on your own website. Copy the code below.

<a href="https://aeo-audit.rezolve.com/us/finance/sqril.io"><img src="https://aeo-audit.rezolve.com/finance/badges/sqril.io.svg" alt="Overall score 46 of 100, Finance AI Visibility Study 2026" width="280" height="64"></a>
Next step

Want AI assistants to name your company?

Book a 30-minute demo to see Rezolve Ai in action and what it can do for your business.

Request a demo