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.

SWIFT47/60TRANSUNION46/60EXPERIAN42/60COINSTAR41/60NAVY FEDERAL CREDIT UNION41/60ZELLE41/60BLOOMBERG L.P.38/60TRADINGVIEW38/60BANCO POPULAR DE PUERTO RICO37/60PAYPAL37/60VENMO37/60CHEXSYSTEMS33/60EQUIFAX33/60MORNINGSTAR32/60S&P GLOBAL31/60ALPACA MARKETS30/60COINBASE30/60PINWHEEL29/60STRIPE29/60XERO29/60ACORNS28/60AFFIRM28/60PAYFAST (PAYGATE)28/60PAYONEER28/60INTERACTIVE BROKERS26/60CHARLES SCHWAB19/60THE HARTFORD9/60MOODY'S21/60CME GROUP19/60ACCENTURE11/60CHUBB10/60MORGAN STANLEY6/60AMERICAN EXPRESS14/60SYNCHRONY FINANCIAL12/60FACTSET20/60NASDAQ19/60ALLSTATE11/60WELLS FARGO18/60PAYCHEX10/60ARES MANAGEMENT3/60
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MethodDemo
Back to the study
AI visibility statementFinance AI Visibility Study 2026Issued October 14, 2026
Account holder

AlphaPoint

alphapoint.com

Stablecoins and digital asset infrastructureCrypto and digital assets

Money20/20 attendee

Statement period
October 9, 2026
when the AI assistants were asked
Account no.
1,288 of 2,219
its rank by overall score
Place in its category
53rd of 80 digital asset infrastructure companies
Closing balance

Named in

0of 60, its tower is dark

by 0 of 4 assistants

Statement note

What this means for AlphaPoint

AI assistants do not name this digital asset infrastructure company in any of their 60 answers. Its overall score is 27 out of 100, which ranks 1,288th of 2,219 companies. The website passes 5 of 14 technical checks for readiness with AI tools.

We asked 15 unbranded questions about its market, so no question mentioned AlphaPoint by name. AI assistants named it in none of the 60 answers. Counting only how often it is named, it ranks 67th of 102 in its sector. The typical crypto and digital asset 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
27Overall score
  • Visibility0
  • Citations1
  • Sentiment50
  • Site quality80
  • 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
66 of 102
by overall score, where the typical crypto and digital asset company scores 30

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Line itemsSection 01

Every question, and where the company came up

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

  1. 01What are good options for fintechs that want to avoid comprehensive digital asset infrastructure suites?0/4
  2. 02How much do institutional-grade digital asset platforms typically cost per year in the US?0/4
  3. 03What are typical use-cases for on-chain finance platforms in large financial institutions?0/4
  4. 04How are governments using digital asset infrastructure for efficient payment processing?0/4
  5. 05What are the top digital asset infrastructure platforms for banks and fintech firms in the US?0/4
  6. 06Is it worth investing in an institutional-grade platform for managing stablecoin payments and trading?0/4
  7. 07Are there simpler alternatives to institutional-grade digital asset liquidity management systems?0/4
  8. 08How does a digital asset financial infrastructure platform compare to traditional banking infrastructure for handling large-scale transactions?0/4
  9. 09Alternatives to all-in-one digital asset financial infrastructure platforms for managing stablecoins and payments0/4
  10. 10How to resolve transaction delays in digital asset treasury management systems?0/4
  11. 11Digital asset trading platforms vs. multi-asset treasury solutions—what's better for financial institutions?0/4
  12. 12What affects the cost of deploying a full-featured digital asset treasury platform for an exchange?0/4
  13. 13Best platforms for managing digital asset treasury and payments in a regulated environment0/4
  14. 14Do banks benefit from adopting digital asset financial infrastructure platforms for liquidity management?0/4
  15. 15Common issues when integrating a digital asset trading platform into existing bank systems0/4
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 Gemini actually said

The company is not named in this answer

Geminidid not name the company

“What are good options for fintechs that want to avoid comprehensive digital asset infrastructure suites?”

Fintechs looking to avoid comprehensive digital asset infrastructure suites have several good options that prioritize modularity, specific functionalities, and integration with existing systems. This approach allows them to adopt digital asset capabilities without building the entire stack in-house, which can be resource-intensive and time-consuming.

Here are some key options and considerations:

1. Modular Infrastructure Layers:

Many providers offer modular solutions that allow fintechs to pick and choose the digital asset services they need. These often function as API-driven backend sy …

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
    Fireblocks
    22
  2. 02
    BitGo
    18
  3. 03
    Anchorage Digital
    18
  4. 04
    Copper
    8

Share of mentions

CompanyShare
  1. Fireblocks
    37.0%
  2. BitGo
    30.4%
  3. Anchorage Digital
    28.3%
  4. Copper
    4.3%
  5. AlphaPoint
    0.0%
  6. Prime Trust
    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
    fireblocks.com
    26
  2. 02
    chain.link
    14
  3. 03
    bitgo.com
    11
  4. 04
    treasury.ripple.com
    11
  5. 05
    fuze.finance
    9
  6. 06
    flow.db.com
    8
  7. 07
    walletinvestor.com
    8
  8. 08
    jpmorgan.com
    6
  9. 09
    alphapoint.com (its own website)
    6
  10. 10
    morganstanley.com
    6

AlphaPoint is in the study as a digital asset infrastructure company.

By assistantSection 05

Which AI assistants named the company

Answers naming it, out of answers received

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

How AlphaPoint 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
80

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 crypto and digital asset companies

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

Overall score
27
Ranks 66 of 102. Typical company: 30
Named in answers
0.0%
Ranks 67 of 102. Typical company: 1.7%
AI readiness
36
Ranks 21 of 102. Typical company: 33
Against its categorySection 08

Compared with digital asset infrastructure companies

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

Overall score
27
Ranks 51 of 80. Typical company: 29
Named in answers
0.0%
Ranks 51 of 80. Typical company: 1.7%
AI readiness
36
Ranks 16 of 80. 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. AlphaPoint 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
25 of 100
  • Markdown negotiationNot met

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

    study: 6.2%
  • llms.txtPartly 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 21 of 100 · 97% of checks could run · checked on October 9, 2026 · alphapoint.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

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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End of statement
All 2,219 companiesHow we measured this
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