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

Named in

5of 60 answers

by 2 of 4 assistants

Statement note

What this means for Circit

AI assistants name Circit in 8.3% of answers, which is more often than the typical company in its sector at 1.7%. Its overall score is 31 out of 100, ranking 810th of 2,219 companies. Its website passes 5 of 14 technical checks for readiness for AI tools.

We asked 15 unbranded questions about its market, so no question mentioned Circit 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
31Overall score
  • Visibility13
  • Citations6
  • Sentiment50
  • Site quality73
  • AI readiness36
Summary of account
Named by AI in
8.3%
5 of 60 answers
Share of mentions
23.8%
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
237 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

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

  1. 01Common issues when verifying transactions using Open Banking tools in audit workflows0/4
  2. 02Are there cost differences between all-in-one audit automation platforms and single-feature tools?0/4
  3. 03How can fund service providers streamline audit confirmation processes using technology?1/4
  4. 04What options exist for US audit firms seeking to replace email-based confirmation workflows?2/4
  5. 05Should US audit firms invest in tools that combine e-signature and independent verification features?0/4
  6. 06Open Banking transaction verification vs direct data extraction for audit procedures0/4
  7. 07How does automated financial statement verification differ from traditional paper-based confirmations?0/4
  8. 08Why might automated audit evidence collection fail to connect with certain financial institutions?0/4
  9. 09Is it worth adopting a centralized platform for PBC collaboration and audit confirmations?1/4
  10. 10What is the typical pricing structure for independent verification platforms in the US?0/4
  11. 11Alternatives to manual confirmation request processes for auditors1/4
  12. 12Ways to improve efficiency in managing bulk confirmation requests for audits0/4
  13. 13Best solutions for managing audit confirmation requests in large US accounting firms0/4
  14. 14What are the top platforms for automating independent evidence collection in financial audits?0/4
  15. 15How can centralized e-signature and transaction verification reduce audit risks for financial institutions?0/4
Total namedOpenAI: 1/15Claude: 0/15Perplexity: 0/15Gemini: 4/15All 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

“How can fund service providers streamline audit confirmation processes using technology?”

Fund service providers can significantly streamline audit confirmation processes using various technological solutions, moving away from time-consuming manual methods. This not only enhances efficiency but also improves security, accuracy, and compliance.

Here's how technology can be leveraged:

Electronic Confirmation Platforms:

Centralized Hubs: Platforms like Circit and Confirmation.com act as secure networks where auditors, fund administrators, custodians, and other stakeholders can exchange financial information directly. This eliminates the need for emails, faxes, or …

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
    Suralink
    1

Share of mentions

CompanyShare
  1. Audit Confirmations (by AuditConfirmations.com)
    47.6%
  2. Circit
    23.8%
  3. Confirmation (by Thomson Reuters)
    23.8%
  4. Suralink
    4.8%
  5. Validis
    0.0%
  6. Capital Confirmation (by Confirmation.com)
    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
    circit.io (its own website)
    16
  2. 02
    tax.thomsonreuters.com
    13
  3. 03
    confirmation.com
    10
  4. 04
    wolterskluwer.com
    8
  5. 05
    cpa.com
    8
  6. 06
    us.confirmation.com
    6
  7. 07
    pcaobus.org
    6
  8. 08
    ustechautomations.com
    5
  9. 09
    auditconfirm.com
    5
  10. 10
    gitnux.org
    4

Circit 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
4/15
OpenAI
1/15
Claude
0/15
Perplexity
0/15
Market comparisonSection 06

How Circit 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
13

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

Citations
6

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
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 financial technology and data companies

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

Overall score
31
Ranks 237 of 574. Typical company: 29
Named in answers
8.3%
Ranks 130 of 574. Typical company: 1.7%
AI readiness
36
Ranks 83 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
31
Ranks 104 of 315. Typical company: 28
Named in answers
8.3%
Ranks 52 of 315. Typical company: 1.7%
AI readiness
36
Ranks 40 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
Can an AI agent check out here?

Not by itself. Circit 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
36 of 100
  • robots.txtNot met

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

    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 26 of 100 · 97% of checks could run · checked on October 9, 2026 · circit.io · 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%
  • 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%
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ShareSection 11

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Overall score 31 of 100 badge for Circit

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/circit.io"><img src="https://aeo-audit.rezolve.com/finance/badges/circit.io.svg" alt="Overall score 31 of 100, Finance AI Visibility Study 2026" width="280" height="64"></a>
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