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.
730 of 2,219
its rank by overall score
Closing balance

Named in

5of 60 answers

by 3 of 4 assistants

Statement note

What this means for Eltropy

AI assistants name this fintech infrastructure company in 8.3% of answers, which is more often than the typical company in its sector at 1.7%. Its overall score is 33 out of 100, ranking 730th of 2,219 in the study. The company's website passes 1 of 14 technical checks for readiness for AI tools.

We asked 15 unbranded questions about its market, so no question mentioned Eltropy by name. AI assistants named it in 5 of the 60 answers. Counting only how often it is named, it ranks 130th of 574 in its sector. The typical financial technology and data company is named in 1.7% of answers.

Overall score
33Overall score
  • Visibility12
  • Citations1
  • Sentiment75
  • Site quality80
  • AI readiness7
Summary of account
Named by AI in
8.3%
5 of 60 answers
Share of mentions
21.7%
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
221 of 574
by overall score, where the typical financial technology and data company scores 29

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Line itemsSection 01

Every question, and where the company came up

Eltropy came up on 4 of 15 questions. Open any window to read that answer.

  1. 01What are the best AI-powered customer service solutions for credit unions and community banks?2/4
  2. 02Are there non-AI methods to automate consumer request management in credit unions?0/4
  3. 03AI-driven customer service platforms vs traditional call centers for credit unions – what's the difference?0/4
  4. 04Why might an AI agent platform fail to process member requests accurately?0/4
  5. 05Do AI-driven agent solutions for credit unions offer tiered pricing based on user volume?0/4
  6. 06Is investing in an AI customer service platform worth it for a small community bank?0/4
  7. 07What features should credit unions look for in an AI-driven conversation automation solution?1/4
  8. 08Automated conversation management vs live agent support for handling routine requests – which is more efficient?0/4
  9. 09How do credit unions use AI platforms to streamline loan application processing?0/4
  10. 10What alternatives exist to AI-powered conversation platforms for handling member service at community banks?1/4
  11. 11How are AI customer service platforms for financial institutions typically priced in the US?0/4
  12. 12How can AI agent platforms improve consumer engagement in community banking?0/4
  13. 13How can a community bank troubleshoot issues with automated consumer request handling?0/4
  14. 14What manual solutions still work for customer service in small banks and credit unions besides automation?1/4
  15. 15What are examples of automating routine consumer inquiries using AI in banking environments?0/4
Total namedOpenAI: 0/15Claude: 1/15Perplexity: 1/15Gemini: 3/15All assistants: 5/60
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

An answer that names the company

Gemininamed the company

“What manual solutions still work for customer service in small banks and credit unions besides automation?”

While automation and digital solutions are increasingly prevalent in banking, several manual, high-touch solutions remain effective for customer service in small banks and credit unions:

In-Person Interactions and Branch Services:

Face-to-Face Problem Resolution: Many customers, especially older generations, still prefer to visit a branch and speak with a member service representative (MSR) to resolve issues eltropy.com. This allows for immediate visual cues and a sense of underst …

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
    Glia
    4
  2. 02
    Kasisto
    4
  3. 03
    Finn AI
    1
  4. 04
    Interface.ai
    1

Share of mentions

CompanyShare
  1. Kasisto
    26.1%
  2. Interface.ai
    26.1%
  3. Eltropy
    21.7%
  4. Glia
    21.7%
  5. Finn AI
    4.3%
  6. Coconut Software
    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
    usefini.com
    10
  2. 02
    thelevel.ai
    10
  3. 03
    glia.com
    7
  4. 04
    lorikeetcx.ai
    7
  5. 05
    bonadio.com
    7
  6. 06
    bland.ai
    6
  7. 07
    agentiveaiq.com
    6
  8. 08
    gradient-labs.ai
    5
  9. 09
    layer3labs.io
    4
  10. 10
    creatio.com
    4

Eltropy is in the study as a fintech infrastructure company.

By assistantSection 05

Which AI assistants named the company

Answers naming it, out of answers received

Gemini
3/15
Claude
1/15
Perplexity
1/15
OpenAI
0/15
Market comparisonSection 06

How Eltropy 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
1

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

Sentiment
75

How positively AI describes the company

Site quality
80

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 financial technology and data companies

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

Overall score
33
Ranks 221 of 574. Typical company: 29
Named in answers
8.3%
Ranks 130 of 574. Typical company: 1.7%
AI readiness
7
Ranks 533 of 574. Typical company: 29
Against its categorySection 08

Compared with fintech infrastructure companies

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

Overall score
33
Ranks 95 of 315. Typical company: 28
Named in answers
8.3%
Ranks 52 of 315. Typical company: 1.7%
AI readiness
7
Ranks 293 of 315. 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 0: Not yet agent-ready. Agents struggle to find basic information about the site.

To reach level 1:
  • 2 of robots.txt, Sitemap, Link headers

Some checks could not run. With them, up to level 3 would be possible.

The website turns away requests that do not come from a browser. AI agents that say what they are meet the same refusal.

Can an AI agent check out here?

Not by itself. Eltropy 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
85 of 100
  • robots.txtCould not check

    Publish a valid robots.txt with crawl rules and a Sitemap line.

    study: 86.1%
  • SitemapPartly met

    Serve an XML sitemap and reference it from robots.txt.

    study: 87.9%
  • Link headersCould not check

    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 negotiationCould not check

    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
  • 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 AuthNot present

    Only relevant if you run your own agents or crawlers: publish a signing key directory.

    study: 0.3%
APIs, auth and MCP
18 of 100
  • API CatalogNot met

    List public APIs in a linkset at /.well-known/api-catalog.

    study: 1.3%
  • OAuth discoveryPartly met

    Publish OpenID Connect or OAuth server metadata under /.well-known.

    study: 6.3%
  • OAuth Protected ResourcePassed

    Metadata telling agents which authorization server to use.

    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 · 51% of checks could run · checked on October 9, 2026 · eltropy.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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ShareSection 11

Share this result

Overall score 33 of 100 badge for Eltropy

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/eltropy.com"><img src="https://aeo-audit.rezolve.com/finance/badges/eltropy.com.svg" alt="Overall score 33 of 100, Finance AI Visibility Study 2026" width="280" height="64"></a>
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