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.
958 of 2,219
its rank by overall score
Place in its category
70th of 203 payment processors
Closing balance

Named in

1of 60 answers

by 1 of 4 assistants

Statement note

What this means for i2c

AI assistants rarely name this payment processor in their answers, with just 1 out of 60 answers mentioning it, often alongside Marqeta or Q2. Its overall score is 29 out of 100, ranking 958th of 2,219 companies, slightly above the typical company in its sector. The company's website passes 4 of 14 technical checks for AI tool readiness.

We asked 15 unbranded questions about its market, so no question mentioned i2c by name. AI assistants named it in 1 of the 60 answers. Counting only how often it is named, it ranks 133rd 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
29Overall score
  • Visibility3
  • Citations0
  • Sentiment50
  • Site quality80
  • AI readiness43
Summary of account
Named by AI in
1.7%
1 of 60 answers
Share of mentions
6.3%
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
135 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

i2c came up on 1 of 15 questions. Open any window to read that answer.

  1. 01What are the most innovative banking and payment technology platforms for financial institutions in the US?1/4
  2. 02What factors can influence the monthly costs of running a cloud-based payments engine?0/4
  3. 03How do modern payments platforms enhance customer experience compared to traditional solutions?0/4
  4. 04Best practices for launching a new card program using a flexible banking technology platform?0/4
  5. 05Composable banking platforms vs legacy systems: what are the main differences?0/4
  6. 06How can banks resolve issues with digital wallet compatibility on advanced payments platforms?0/4
  7. 07Is switching to a next-generation banking infrastructure worth the investment for mid-sized financial firms?0/4
  8. 08Alternatives to all-in-one banking and payment platforms for community banks0/4
  9. 09Unified payment technology platforms vs modular solutions: which is better for scaling fintech products?0/4
  10. 10How can credit unions use composable banking tools to quickly roll out new financial products?0/4
  11. 11Typical pricing models for enterprise-grade banking technology platforms in the US?0/4
  12. 12Common challenges when integrating a cloud-based payment processing platform?0/4
  13. 13Best banking technology solutions for accelerating digital transformation in financial services?0/4
  14. 14Top features to look for in a modern, unified banking-as-a-service platform?0/4
  15. 15What options exist for fintechs needing customizable payments infrastructure besides unified platforms?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

“What are the most innovative banking and payment technology platforms for financial institutions in the US?”

The most innovative US banking and payment platforms are not one-size-fits-all: FIS, Fiserv, Jack Henry, Temenos, Finastra, i2c, Marqeta, Stripe, Modern Treasury, and The Clearing House RTP stand out across core banking, embedded finance, card issuing, payment operations, and instant payments. Selection should depend on whether the institution needs to modernize its core, launch products quickly, or improve payment infrastructure.

Leading platforms by use case

Platform · Best fit · Why it stands out

FIS · Large banks and diversified financial institutions · Bro …

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
    Marqeta
    4
  2. 02
    Q2
    3

Share of mentions

CompanyShare
  1. Marqeta
    31.3%
  2. Q2
    31.3%
  3. FIS (Fidelity National Information Services) Modern Banking Platform
    18.8%
  4. Galileo Financial Technologies
    12.5%
  5. i2c
    6.3%
  6. Green Dot Corporation (Banking as a Service)
    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
    backbase.com
    10
  2. 02
    finantrix.com
    7
  3. 03
    mckinsey.com
    7
  4. 04
    mambu.com
    6
  5. 05
    fisglobal.com
    6
  6. 06
    linkedin.com
    5
  7. 07
    openbankingtracker.com
    5
  8. 08
    decta.com
    5
  9. 09
    gartner.com
    5
  10. 10
    stripe.com
    4

i2c is in the study as a payment processor.

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 i2c 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
3

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
43

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
29
Ranks 135 of 375. Typical company: 27
Named in answers
1.7%
Ranks 133 of 375. Typical company: 0.0%
AI readiness
43
Ranks 15 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
29
Ranks 66 of 203. Typical company: 27
Named in answers
1.7%
Ranks 64 of 203. Typical company: 0.0%
AI readiness
43
Ranks 8 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. i2c 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
25 of 100
  • Markdown negotiationNot met

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

    study: 6.2%
  • llms.txtPartly 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 29 of 100 · 97% of checks could run · checked on October 9, 2026 · www.i2cinc.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

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%
  • Not metHTTP 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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