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.
1,149 of 2,219
its rank by overall score
Closing balance

Named in

0of 60, its tower is dark

by 0 of 4 assistants

Statement note

What this means for HyperVerge

AI assistants do not name this fraud and identity company in any of their 60 answers, while they often name others such as Jumio and Onfido. Its overall score is 28 out of 100, ranking 1,149th of 2,219 companies. The website passes 5 out of 14 technical checks for AI tool readiness.

We asked 15 unbranded questions about its market, so no question mentioned HyperVerge by name. AI assistants named it in none of the 60 answers. Counting only how often it is named, it ranks 334th of 574 in its sector. The typical financial technology and data company is named in 1.7% 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
28Overall score
  • Visibility0
  • Citations1
  • Sentiment50
  • Site quality87
  • AI readiness36
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
5/14
technical checks passed. Typical for its sector: 4
Rank in its sector
302 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

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

  1. 01How can I resolve high customer drop-off rates during online KYC verification?0/4
  2. 02How are digital onboarding solutions priced for small banks compared to large enterprises?0/4
  3. 03Best alternatives to AI-powered liveness checks for fraud prevention in digital onboarding?0/4
  4. 04What are options for digital KYC if I want to avoid video call-based verification methods?0/4
  5. 05Document verification vs face authentication for digital KYC: which is more effective for fraud prevention?0/4
  6. 06Ways to prevent synthetic identity fraud using digital KYC in the US market?0/4
  7. 07What is the typical cost structure for identity verification APIs for US fintechs?0/4
  8. 08Active liveness detection vs passive liveness: which is more secure for online customer verification?0/4
  9. 09Alternatives to face authentication for digital identity verification in online banking?0/4
  10. 10Top identity verification platforms for seamless customer onboarding in fintech?0/4
  11. 11Are AI-powered digital KYC platforms a good choice for scaling customer onboarding in insurance companies?0/4
  12. 12What should I do if passive liveness checks frequently fail during remote onboarding?0/4
  13. 13Is investing in advanced face authentication technology worth it for a mid-sized lender?0/4
  14. 14What are the best digital KYC solutions for banks in the US?0/4
  15. 15How do financial institutions use OCR for bank statements and payslips in customer onboarding?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 OpenAI actually said

The company is not named in this answer

OpenAIdid not name the company

“What is the typical cost structure for identity verification APIs for US fintechs?”

Short answer

Typical identity-verification API pricing for US fintechs is usage-based with volume tiers plus a few fixed charges. Headline per-check rates you’ll see range roughly from ~$0.10 up to $2.00 (and occasionally higher for premium checks), with monthly minimums, platform/subscription fees, and extra line-item charges for document / biometrics / watchlist checks and support/SLAs. (signzy.com)

What the cost structure normally includes (breakdown)

1. Per-check (transactional) fees

The main cha …

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
    Jumio
    7
  2. 02
    Socure
    6
  3. 03
    Onfido
    4
  4. 04
    Persona
    4

Share of mentions

CompanyShare
  1. Jumio
    31.0%
  2. Socure
    27.6%
  3. Onfido
    24.1%
  4. Persona
    17.2%
  5. HyperVerge
    0.0%
  6. ID.me
    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
    nhimg.org
    12
  2. 02
    didit.me
    12
  3. 03
    microblink.com
    8
  4. 04
    binderr.com
    6
  5. 05
    regulaforensics.com
    6
  6. 06
    shuftipro.com
    6
  7. 07
    zyphe.com
    5
  8. 08
    signzy.com
    5
  9. 09
    plaid.com
    4
  10. 10
    linkedin.com
    4

HyperVerge 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

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

How HyperVerge 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
1

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

Sentiment
50

How positively AI describes the company

Site quality
87

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
28
Ranks 302 of 574. Typical company: 29
Named in answers
0.0%
Ranks 334 of 574. Typical company: 1.7%
AI readiness
36
Ranks 83 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
28
Ranks 97 of 171. Typical company: 30
Named in answers
0.0%
Ranks 103 of 171. Typical company: 1.7%
AI readiness
36
Ranks 35 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 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. HyperVerge 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 · hyperverge.co · 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 20 AI crawlers by name. All others follow its general rules.

Training AI

  • GPTBot*allowed
  • ClaudeBot*allowed
  • Anthropic-AI*allowed
  • Google-Extended*allowed
  • Applebot-Extended*allowed
  • Meta-ExternalAgent*allowed
  • FacebookBot*allowed
  • Bytespider*allowed
  • CCBot*allowed
  • Diffbotpartly
  • Omgilibotpartly

AI search

  • OAI-SearchBot*allowed
  • Claude-SearchBot*allowed
  • PerplexityBot*allowed
  • Applebot*allowed
  • Amazonbot*allowed
  • YouBot*allowed

Answering questions

  • ChatGPT-User*allowed
  • Claude-User*allowed
  • Perplexity-User*allowed
  • DuckAssistBot*allowed
  • MistralAI-User*allowed

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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