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

Named in

4of 60 answers

by 3 of 4 assistants

Statement note

What this means for Veridocs

AI assistants name this fraud and identity company in 6.7% of answers, more often than the typical company in its sector at 1.7%. Its overall score is 39 out of 100, ranking 341st of 2,219. The company's website passes 2 out of 14 technical checks for AI tool readiness.

We asked 15 unbranded questions about its market, so no question mentioned Veridocs by name. AI assistants named it in 4 of the 60 answers. Counting only how often it is named, it ranks 155th of 574 in its sector. The typical financial technology and data company is named in 1.7% of answers.

Overall score
39Overall score
  • Visibility14
  • Citations1
  • Sentiment100
  • Site quality80
  • AI readiness14
Summary of account
Named by AI in
6.7%
4 of 60 answers
Share of mentions
36.4%
of the mentions of it and its 5 peers
AI readiness
2/14
technical checks passed. Typical for its sector: 4
Rank in its sector
94 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

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

  1. 01Non-digital methods for on-site identity authentication in high-security areas0/4
  2. 02Manual versus automated ID authentication for secure facility access0/4
  3. 03Physical document scanning vs biometric verification for identity checks0/4
  4. 04What are the best physical ID authentication solutions for casinos?2/4
  5. 05Are there affordable options for implementing in-person ID authentication at secure sites?0/4
  6. 06Alternatives to automated physical ID scanners for fraud prevention0/4
  7. 07Typical cost range for physical ID verification solutions for midsize organizations0/4
  8. 08Which identity verification systems are proven effective for detecting counterfeit documents?1/4
  9. 09Why might a physical document authentication system fail to detect counterfeit IDs?0/4
  10. 10Best practices for integrating physical ID verification into casino entry processes1/4
  11. 11How reliable are real-time physical ID fraud detection systems?0/4
  12. 12How do banks use physical ID authentication to comply with regulatory requirements?0/4
  13. 13Top-rated fraud detection technology for banks requiring in-person ID checks0/4
  14. 14Is investing in in-person ID verification technology worth it for financial institutions?0/4
  15. 15What are common issues with physical ID scanners in busy environments?0/4
Total namedOpenAI: 1/15Claude: 1/15Perplexity: 0/15Gemini: 2/15All assistants: 4/60
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 OpenAI actually said

An answer that names the company

OpenAInamed the company

“What are the best physical ID authentication solutions for casinos?”

Short answer — there’s no single “best” product; casinos typically use a layered approach combining (A) a physical ID/document-scanner with active document-authentication checks, (B) a face/biometric match between the patron and the ID, and (C) access-control / patron-management integration (self‑exclusion, banned lists, loyalty accounts, AML/CRM). The vendors most frequently used and recommended for high-throughput casino environments are Veridocs, IDScan/VeriScan, Patronscan, eConnect (and similar casino‑focused integrators), plus enterprise identity platforms (Jumio, Entrust, LexisNexis) fo …

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
    IDScan.net
    1
  2. 02
    Mitek Systems
    1

Share of mentions

CompanyShare
  1. Veridocs
    36.4%
  2. IDScan.net
    36.4%
  3. Mitek Systems
    18.2%
  4. E-Seek
    9.1%
  5. Acuant (by GBG)
    0.0%
  6. Adaptive Recognition
    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
    idscan.net
    11
  2. 02
    regulaforensics.com
    8
  3. 03
    vouched.id
    6
  4. 04
    didit.me
    6
  5. 05
    pingidentity.com
    6
  6. 06
    1kosmos.com
    4
  7. 07
    arxiv.org
    4
  8. 08
    jumio.com
    4
  9. 09
    startwithidentity.com
    4
  10. 10
    checkfile.ai
    4

Veridocs is in the study as a fraud and identity company.

By assistantSection 05

Which AI assistants named the company

Answers naming it, out of answers received

Gemini
2/15
Claude
1/15
OpenAI
1/15
Perplexity
0/15
Market comparisonSection 06

How Veridocs 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
14

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
100

How positively AI describes the company

Site quality
80

How well built the website's own pages are

AI readiness
14

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
39
Ranks 94 of 574. Typical company: 29
Named in answers
6.7%
Ranks 155 of 574. Typical company: 1.7%
AI readiness
14
Ranks 504 of 574. Typical company: 29
Against its categorySection 08

Compared with fraud and identity companies

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

Overall score
39
Ranks 33 of 171. Typical company: 30
Named in answers
6.7%
Ranks 43 of 171. Typical company: 1.7%
AI readiness
14
Ranks 156 of 171. Typical company: 36
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. Veridocs 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
0 of 100
  • robots.txtNot met

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

    study: 86.1%
  • SitemapNot 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
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
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 7 of 100 · 97% of checks could run · checked on October 9, 2026 · www.veridocs.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

2 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%
  • 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

  • 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 39 of 100 badge for Veridocs

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/veridocs.com"><img src="https://aeo-audit.rezolve.com/finance/badges/veridocs.com.svg" alt="Overall score 39 of 100, Finance AI Visibility Study 2026" width="280" height="64"></a>
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