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.
1,807 of 2,219
its rank by overall score
Place in its category
145th 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 JSC Georgian Card

AI assistants do not name this payment processor in any of the 60 answers, while they occasionally name others such as Fiserv and IDEMIA. The company has an overall score of 25 out of 100, ranking 1,807th of 2,219 companies. Its website passes 4 of 14 technical checks measuring how ready it is for AI tools.

We asked 15 unbranded questions about its market, so no question mentioned JSC Georgian Card 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
25Overall score
  • Visibility0
  • Citations0
  • Sentiment50
  • Site quality73
  • AI readiness29
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
4/14
technical checks passed. Typical for its sector: 4
Rank in its sector
280 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

JSC Georgian Card came up on 0 of 15 questions. Open any window to read that answer.

  1. 01Common issues when integrating card processing services with core banking systems0/4
  2. 02Are there cost differences between cloud-based and on-premises card processing services?0/4
  3. 03Ways banks can use card tokenization to improve payment security for their clients0/4
  4. 04Alternatives to outsourcing payment card personalization for midsize banks0/4
  5. 05Is investing in in-house card processing systems worth it for regional banks?0/4
  6. 06How does secure chip card personalization compare to magnetic stripe options?0/4
  7. 07What are the top payment card processing solutions for banks in the US?0/4
  8. 08What are some non-traditional methods for secure bank card processing?0/4
  9. 09What factors should financial institutions consider before upgrading payment card personalization technology?0/4
  10. 10Card tokenization services vs traditional EMV processing—key differences for banks?0/4
  11. 11Which payment card processing providers offer the most flexible APIs for US financial institutions?0/4
  12. 12Best card personalization services for financial institutions looking to enhance their product offerings0/4
  13. 13What is the typical price range for full-service card processing and personalization for banks?0/4
  14. 14How can microfinance organizations streamline card issuance for new customers?0/4
  15. 15What can cause delays in payment card personalization and how can they be addressed?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 Gemini actually said

The company is not named in this answer

Geminidid not name the company

“Alternatives to outsourcing payment card personalization for midsize banks”

Midsize banks exploring alternatives to outsourcing payment card personalization have several options that offer varying degrees of control, flexibility, and investment. The "right" approach depends on the bank's specific needs, card portfolio, growth strategy, and desired customer experience.

Here are some alternatives and related considerations:

1. In-House Card Personalization (Self-Issuance)

Bringing card personalization in-house, also known as self-issuance, gives banks greater control over data, potentially improved profitability, and the ability to personalize products in real ti …

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
    Fiserv
    6
  2. 02
    IDEMIA
    4
  3. 03
    CPI Card Group
    2
  4. 04
    FIS (Fidelity National Information Services)
    1

Share of mentions

CompanyShare
  1. Fiserv
    35.7%
  2. FIS (Fidelity National Information Services)
    25.0%
  3. IDEMIA
    17.9%
  4. TSYS (A Global Payments Company)
    10.7%
  5. CPI Card Group
    10.7%
  6. JSC Georgian Card
    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
    mastercard.com
    9
  2. 02
    gi-de.com
    8
  3. 03
    entrust.com
    7
  4. 04
    fisglobal.com
    7
  5. 05
    dashdevs.com
    6
  6. 06
    linkedin.com
    6
  7. 07
    wisecardglobal.com
    5
  8. 08
    finantrix.com
    5
  9. 09
    cpicardgroup.com
    5
  10. 10
    idemia.com
    5

JSC Georgian Card 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 JSC Georgian Card 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
73

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 cards and payments companies

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

Overall score
25
Ranks 280 of 375. Typical company: 27
Named in answers
0.0%
Ranks 179 of 375. Typical company: 0.0%
AI readiness
29
Ranks 106 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
25
Ranks 142 of 203. Typical company: 27
Named in answers
0.0%
Ranks 91 of 203. Typical company: 0.0%
AI readiness
29
Ranks 59 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.

  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. JSC Georgian Card 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 · gc.ge · 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

  • 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%
  • 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

  • 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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