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.
990 of 2,219
its rank by overall score
Place in its category
13th of 32 digital banks
Closing balance

Named in

0of 60, its tower is dark

by 0 of 4 assistants

Statement note

What this means for Jupiter Money

AI assistants do not name this digital bank in any of their 60 answers; they mention companies like Chime, Current and Varo Bank instead. Jupiter Money has an overall score of 29 out of 100, which ranks 990th of 2,219 companies and is about the same as the typical company in its sector. Its website passes 4 out of 14 technical checks for readiness for AI tools.

We asked 15 unbranded questions about its market, so no question mentioned Jupiter Money by name. AI assistants named it in none of the 60 answers. Counting only how often it is named, it ranks 188th of 394 in its sector. The typical banking 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
  • Visibility0
  • Citations0
  • Sentiment50
  • Site quality93
  • 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: 3
Rank in its sector
143 of 394
by overall score, where the typical banking company scores 28

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Line itemsSection 01

Every question, and where the company came up

Jupiter Money came up on 0 of 15 questions. Open any window to read that answer.

  1. 01Are mobile banking platforms with integrated rewards programs a good choice?0/4
  2. 02How can digital banking apps help simplify paying rent and utilities?0/4
  3. 03Ways to use mobile banking apps for automatic savings and investment0/4
  4. 04How to resolve failed money transfers in digital personal finance apps?0/4
  5. 05Are online-only banking apps safer than using traditional banks' mobile features?0/4
  6. 06How do neobanks compare to credit unions for personal finance management?0/4
  7. 07What should I do if I can't link an account to my digital banking app?0/4
  8. 08Best digital banking apps for tracking spending and budgeting0/4
  9. 09Digital banking apps vs traditional bank mobile apps for managing finances0/4
  10. 10What are some top-rated online-only savings account apps in the US?0/4
  11. 11Alternatives to all-in-one personal finance management apps0/4
  12. 12What is the typical fee structure for digital banking platforms in the US?0/4
  13. 13What are some options if I want a digital banking experience without a dedicated app?0/4
  14. 14Do online banking apps offer free checking accounts with no hidden fees?0/4
  15. 15Is opening a zero-balance savings account with a digital banking app worth it?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

“Ways to use mobile banking apps for automatic savings and investment”

I'll search for current information on how mobile banking apps can help with automatic savings and investment features.Based on current mobile banking apps, here are the key ways you can use them for automatic savings and investment:

Round-Up Features

Acorns is known for its round-up approach, where every time you make a purchase with a linked card, it rounds up to the next dollar and invests the difference in a diversified portfolio of low-cost index funds and ETFs. Similarly, Chime's Round Ups feature rounds every debit-card purchase up to the nearest dollar and moves the difference int …

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
    Chime
    9
  2. 02
    Current
    2
  3. 03
    Varo Bank
    1

Share of mentions

CompanyShare
  1. Chime
    45.5%
  2. Ally Bank (Ally Mobile App)
    36.4%
  3. Varo Bank
    18.2%
  4. Jupiter Money
    0.0%
  5. SoFi Money
    0.0%
  6. Current
    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
    forbes.com
    7
  2. 02
    finance.yahoo.com
    7
  3. 03
    nerdwallet.com
    6
  4. 04
    paytm.com
    5
  5. 05
    cnbc.com
    5
  6. 06
    gobankingrates.com
    4
  7. 07
    crediful.com
    4
  8. 08
    chime.com
    4
  9. 09
    usbank.com
    3
  10. 10
    bankrate.com
    3

Jupiter Money is in the study as a digital bank.

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 Jupiter Money 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
93

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 banking companies

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

Overall score
29
Ranks 143 of 394. Typical company: 28
Named in answers
0.0%
Ranks 188 of 394. Typical company: 0.0%
AI readiness
29
Ranks 82 of 394. Typical company: 29
Against its categorySection 08

Compared with digital banks

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

Overall score
29
Ranks 10 of 32. Typical company: 28
Named in answers
0.0%
Ranks 14 of 32. Typical company: 0.0%
AI readiness
29
Ranks 10 of 32. 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. Jupiter Money 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
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
50 of 100
  • Markdown negotiationNot met

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

    study: 6.2%
  • llms.txtPassed

    An llms.txt that tells language models what the site offers.

    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 36 of 100 · 97% of checks could run · checked on October 9, 2026 · jupiter.money · 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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