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.
2,154 of 2,219
its rank by overall score
Place in its category
188th of 203 payment processors
Closing balance

Named in

0of 60, its tower is dark

by 0 of 4 assistants

Statement note

What this means for Fenix International

AI assistants do not name this payment processor in any of the 60 answers. Its overall score is 21 out of 100, ranking 2,154th of 2,219 companies in the study, and it ranks 354th of 375 in its sector. Its website passes 1 of 14 technical checks for AI tool readiness.

We asked 15 unbranded questions about its market, so no question mentioned Fenix International by name. AI assistants named it in none of the 60 answers. Counting only how often it is named, it ranks 179th 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
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
354 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

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

  1. 01Average cost to develop a business mobile app with customer service features0/4
  2. 02Best mobile app development services for businesses looking to scale0/4
  3. 03Alternatives to custom software development for improving customer acquisition0/4
  4. 04Pros and cons of outsourcing software development compared to in-house teams0/4
  5. 05Use cases for integrating payment systems into custom software for US businesses0/4
  6. 06Why is my mobile app project experiencing delays and how can I fix it?0/4
  7. 07What factors affect the price of custom software development in the US?0/4
  8. 08How do I know if my business needs a custom customer management solution?0/4
  9. 09Low-code or no-code solutions as substitutes for traditional app development0/4
  10. 10What are the best custom software development firms for startups in the US?0/4
  11. 11How can custom data management solutions improve customer retention?0/4
  12. 12Common mistakes to avoid when hiring a software development partner0/4
  13. 13Is investing in a bespoke mobile app worth it for mid-sized companies?0/4
  14. 14Top-rated US technology firms specializing in customer management systems0/4
  15. 15Custom software development vs off-the-shelf software: which is better for customer management?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 Claude actually said

The company is not named in this answer

Claudedid not name the company

“Best mobile app development services for businesses looking to scale”

I'll search for current information about the best mobile app development services for scaling businesses.Based on current market research, here are the best mobile app development services for businesses looking to scale:

Top Enterprise-Focused Providers

For businesses scaling operations, companies like Andersen, TELUS Digital, Intellectsoft, Simform, 10Pearls, and ELEKS stand out because they pair mobile engineering with broader capabilities such as compliance expertise.

Merixstudio is best for large, business-critical mobile products; EPAM is best for global, multi-market mobile prog …

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
    BairesDev
    3
  2. 02
    ELEKS
    1
  3. 03
    Iflexion
    1
  4. 04
    Intellectsoft
    1

Share of mentions

CompanyShare
  1. BairesDev
    42.9%
  2. Intellectsoft
    28.6%
  3. ELEKS
    14.3%
  4. Iflexion
    14.3%
  5. Fenix International
    0.0%
  6. Chetu
    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
    linkedin.com
    8
  2. 02
    lowcode.agency
    4
  3. 03
    innowise.com
    3
  4. 04
    appinventiv.com
    3
  5. 05
    clutch.co
    3
  6. 06
    dynamologic.com
    3
  7. 07
    g2.com
    3
  8. 08
    microsoft.com
    3
  9. 09
    kissflow.com
    3
  10. 10
    avibeweb.com
    2

Fenix International is in the study as a payment processor.

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 Fenix International 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 cards and payments companies

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

Overall score
21
Ranks 354 of 375. Typical company: 27
Named in answers
0.0%
Ranks 179 of 375. Typical company: 0.0%
AI readiness
7
Ranks 333 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
21
Ranks 185 of 203. Typical company: 27
Named in answers
0.0%
Ranks 91 of 203. Typical company: 0.0%
AI readiness
7
Ranks 174 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.

This website turned most of our scan away, so it has no level. Only 16% 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
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.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 · 16% of checks could run · checked on October 9, 2026 · fenixinternational.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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