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.

SWIFT47/60TRANSUNION46/60EXPERIAN42/60COINSTAR41/60NAVY FEDERAL CREDIT UNION41/60ZELLE41/60BLOOMBERG L.P.38/60TRADINGVIEW38/60BANCO POPULAR DE PUERTO RICO37/60PAYPAL37/60VENMO37/60CHEXSYSTEMS33/60EQUIFAX33/60MORNINGSTAR32/60S&P GLOBAL31/60ALPACA MARKETS30/60COINBASE30/60PINWHEEL29/60STRIPE29/60XERO29/60ACORNS28/60AFFIRM28/60PAYFAST (PAYGATE)28/60PAYONEER28/60INTERACTIVE BROKERS26/60CHARLES SCHWAB19/60THE HARTFORD9/60MOODY'S21/60CME GROUP19/60ACCENTURE11/60CHUBB10/60MORGAN STANLEY6/60AMERICAN EXPRESS14/60SYNCHRONY FINANCIAL12/60FACTSET20/60NASDAQ19/60ALLSTATE11/60WELLS FARGO18/60PAYCHEX10/60ARES MANAGEMENT3/60
Rezolve Ai
MethodDemo
Back to the study
AI visibility statementFinance AI Visibility Study 2026Issued October 14, 2026
Account holder

Lithic

lithic.com

Payment processors, acquirers and point of saleCards and payments

Money20/20 attendee

Statement period
October 9 to 14, 2026
when the AI assistants were asked
Account no.
556 of 2,219
its rank by overall score
Place in its category
39th of 203 payment processors
Closing balance

Named in

7of 60 answers

by 4 of 4 assistants

Statement note

What this means for Lithic

AI assistants name this payment processor in 11.7% of answers, while the typical company in its sector is not named in any answers. It has an overall score of 36 out of 100, ranking 556th of 2,219 companies. The website passes 5 out of 14 technical checks for readiness for AI tools.

We asked 15 unbranded questions about its market, so no question mentioned Lithic by name. AI assistants named it in 7 of the 60 answers. Counting only how often it is named, it ranks 63rd of 375 in its sector. The typical cards and payments company is named in 0.0% of answers.

Overall score
36Overall score
  • Visibility12
  • Citations3
  • Sentiment83
  • Site quality73
  • AI readiness36
Summary of account
Named by AI in
11.7%
7 of 60 answers
Share of mentions
15.2%
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
75 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

Lithic came up on 3 of 15 questions. Open any window to read that answer.

  1. 01How are transaction and monthly fees typically structured for payment processing platforms in the U.S.?0/4
  2. 02How do direct network connections benefit businesses setting up large-scale card programs?0/4
  3. 03What are the best ways for developers to test card program functionality before going live?0/4
  4. 04How can issuers handle compliance issues when integrating card processing APIs?0/4
  5. 05What features impact the cost of building a custom card program for fintech businesses?0/4
  6. 06What are the best platforms for launching enterprise-level card programs in the United States?1/4
  7. 07Which payment processing solutions offer the most robust fraud controls for fintech developers?0/4
  8. 08Prepaid vs. debit card issuing platforms—what are the pros and cons for digital-first banks?0/4
  9. 09Is an end-to-end card issuing platform worth it for scaling fintech startups?2/4
  10. 10Why might declined transactions happen on newly issued virtual cards?0/4
  11. 11What should banks look for when choosing an enterprise card issuing service?0/4
  12. 12Which API-first platforms are available for rapidly launching virtual card programs?4/4
  13. 13What alternatives exist to cloud-based card issuing for businesses wanting more control?0/4
  14. 14How does card issuing differ from traditional banking payment processing infrastructure?0/4
  15. 15What are some common use cases for programmable card issuing in enterprise environments?0/4
Total namedOpenAI: 2/15Claude: 2/15Perplexity: 2/15Gemini: 1/15All assistants: 7/60
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 best platforms for launching enterprise-level card programs in the United States?”

For most enterprise card programs in the United States, the strongest shortlist is Marqeta, Galileo, Lithic, Stripe Issuing, Highnote, and Adyen Issuing. The best choice depends on whether you need maximum API control, rapid launch, commercial expense features, or a broader payments stack.

Platform · Best for · Main strengths · Key trade-off

Marqeta · Large, highly configurable fintech and embedded-finance programs · Mature APIs, real-time authorization controls, physical and virtual cards, multi-network support · Requires substantial product, compliance, and o …

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
    12
  2. 02
    Stripe Issuing
    7
  3. 03
    Bond
    1
  4. 04
    Galileo Financial Technologies
    1

Share of mentions

CompanyShare
  1. Stripe Issuing
    34.8%
  2. Marqeta
    23.9%
  3. Lithic
    15.2%
  4. Galileo Financial Technologies
    15.2%
  5. Fiserv (Card Services)
    6.5%
  6. Bond
    4.3%
ReferrersSection 04

Websites the AI used as sources

How many times each website was listed as a source in these answers

  1. 01
    stripe.com
    13
  2. 02
    dashdevs.com
    11
  3. 03
    marqeta.com
    7
  4. 04
    lithic.com (its own website)
    7
  5. 05
    enfuce.com
    5
  6. 06
    guideflow.com
    5
  7. 07
    photonpay.com
    4
  8. 08
    buvei.com
    4
  9. 09
    docs.stripe.com
    4
  10. 10
    gitnux.org
    4

Lithic 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
2/15
OpenAI
2/15
Perplexity
2/15
Gemini
1/15
Market comparisonSection 06

How Lithic 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
12

How often AI assistants name the company, and how that compares with its peers

Citations
3

How often AI uses the company's own website as a source

Sentiment
83

How positively AI describes the company

Site quality
73

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 cards and payments companies

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

Overall score
36
Ranks 75 of 375. Typical company: 27
Named in answers
11.7%
Ranks 63 of 375. Typical company: 0.0%
AI readiness
36
Ranks 41 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
36
Ranks 33 of 203. Typical company: 27
Named in answers
11.7%
Ranks 22 of 203. Typical company: 0.0%
AI readiness
36
Ranks 23 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. Lithic 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
63 of 100
  • AI bot rulesPassed

    Explicit robots.txt rules for AI crawlers such as GPTBot, ClaudeBot and PerplexityBot.

    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 32 of 100 · 97% of checks could run · checked on October 9, 2026 · www.lithic.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%
  • Not metllms.txt publishedstudy: 28.1%
  • PassedToken budget (page weight)study: 97.3%

Bot Access Control

  • PassedExplicit 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 rules for 9 AI crawlers by name. All others follow its general rules.

Training AI

  • GPTBot*blocked
  • ClaudeBot*blocked
  • Anthropic-AI*blocked
  • Google-Extended*blocked
  • Applebot-Extended*blocked
  • Meta-ExternalAgent*blocked
  • FacebookBotpartly
  • Bytespider*blocked
  • CCBot*blocked
  • Diffbot*blocked
  • 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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ShareSection 12

Share this result

Overall score 36 of 100 badge for Lithic

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/lithic.com"><img src="https://aeo-audit.rezolve.com/finance/badges/lithic.com.svg" alt="Overall score 36 of 100, Finance AI Visibility Study 2026" width="280" height="64"></a>
End of statement
All 2,219 companiesHow we measured this
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