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.
2,151 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 Cohen Circle

AI assistants do not name this venture capital firm in any of the 60 answers reviewed. Its overall score is 21 out of 100, which ranks 2,151st of 2,219 companies and 231st of 238 in its sector. Its website passes 4 out of 14 technical checks for readiness for AI tools.

We asked 15 unbranded questions about its market, so no question mentioned Cohen Circle by name. AI assistants named it in none of the 60 answers. Counting only how often it is named, it ranks 120th of 238 in its sector. The typical investing and wealth company is named in 0.8% 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
21Overall score
  • Visibility0
  • Citations0
  • Sentiment50
  • Site quality53
  • AI readiness29
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
4/14
technical checks passed. Typical for its sector: 4
Rank in its sector
231 of 238
by overall score, where the typical investing and wealth company scores 28

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Line itemsSection 01

Every question, and where the company came up

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

  1. 01Who provides founder-friendly investment terms besides venture capital and private equity groups?0/4
  2. 02What type of operational expertise can founders expect from strategic investors?0/4
  3. 03How do valuation expectations differ between early-stage and later-stage private equity deals?0/4
  4. 04Typical fees or carried interest percentages in US venture capital deals0/4
  5. 05How can venture funding help a company prepare for exit?0/4
  6. 06What are common pitfalls when negotiating terms with private equity firms?0/4
  7. 07How do growth-stage startups find operational support from investors?0/4
  8. 08Is it worth giving up equity for hands-on startup support from investors?0/4
  9. 09Differences between pre-seed and Series A investment strategies0/4
  10. 10Venture capital vs private equity for scaling a US-based tech company0/4
  11. 11Why do some startups struggle to secure follow-on investments after their seed round?0/4
  12. 12Are long-term investor partnerships better than multiple short funding rounds for startups?0/4
  13. 13Alternatives to traditional venture capital for US entrepreneurs0/4
  14. 14Best funding options for early-stage founders in the US0/4
  15. 15Non-dilutive funding sources for scaling up a startup in the US0/4
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

“Venture capital vs private equity for scaling a US-based tech company”

For a US-based tech company looking to scale, both Venture Capital (VC) and Private Equity (PE) offer distinct advantages and disadvantages. The best choice depends largely on the company's stage of development, growth trajectory, and long-term goals.

Venture Capital (VC)

Best for: Early-stage companies with high growth potential, often pre-profitability, seeking rapid market share.

Characteristics:

Investment Stage: VCs typically invest in early-stage companies (seed, Series A, Series B) that have a product and initial market traction, but may not yet be profitable. …

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.

Share of mentions

CompanyShare
  1. Andreessen Horowitz (a16z)
    50.0%
  2. Sequoia Capital
    25.0%
  3. Accel
    25.0%
  4. Cohen Circle
    0.0%
  5. Greylock Partners
    0.0%
  6. Founders Fund
    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
    qubit.capital
    11
  2. 02
    linkedin.com
    6
  3. 03
    angelinvestorsnetwork.com
    6
  4. 04
    ctacquisitions.com
    5
  5. 05
    allied.vc
    4
  6. 06
    rho.co
    4
  7. 07
    creditforstartups.com
    4
  8. 08
    vcbeast.com
    4
  9. 09
    startups.com
    4
  10. 10
    jpmorgan.com
    3

Cohen Circle is in the study as a venture capital firm.

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 Cohen Circle 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
0

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

Sentiment
50

How positively AI describes the company

Site quality
53

How well built the website's own pages are

AI readiness
29

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 investing and wealth companies

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

Overall score
21
Ranks 231 of 238. Typical company: 28
Named in answers
0.0%
Ranks 120 of 238. Typical company: 0.8%
AI readiness
29
Ranks 51 of 238. Typical company: 29
Against its categorySection 08

Compared with venture capital firms

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

Overall score
21
Ranks 57 of 59. Typical company: 26
Named in answers
0.0%
Ranks 25 of 59. Typical company: 0.0%
AI readiness
29
Ranks 10 of 59. 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 1: Basic web presence. Two of robots.txt, a sitemap and Link headers are in place.

To reach level 2:
  • Content Signals

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. Cohen Circle 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
  • MPPCould not check
  • 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
100 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 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 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 27 of 100 · 92% of checks could run · checked on October 9, 2026 · cohencircle.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

4 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

  • 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%
AI crawlersSection 11

What AI crawlers may read (robots.txt)

This website sets no rules for any AI crawler by name, like 86% of the websites whose rules we could read. Every AI crawler follows its general rules.

Training AI

  • GPTBotpartly
  • ClaudeBotpartly
  • Anthropic-AIpartly
  • Google-Extendedpartly
  • Applebot-Extendedpartly
  • Meta-ExternalAgentpartly
  • FacebookBotpartly
  • Bytespiderpartly
  • CCBotpartly
  • Diffbotpartly
  • Omgilibotpartly

AI search

  • OAI-SearchBotpartly
  • Claude-SearchBotpartly
  • PerplexityBotpartly
  • Applebotpartly
  • Amazonbotpartly
  • YouBotpartly

Answering questions

  • ChatGPT-Userpartly
  • Claude-Userpartly
  • Perplexity-Userpartly
  • DuckAssistBotpartly
  • MistralAI-Userpartly

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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