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

Named in

4of 60 answers

by 4 of 4 assistants

Statement note

What this means for Channel3

AI assistants name this fintech infrastructure company in 6.7% of answers, which is more frequent than the typical company in its sector at 1.7%. It has an overall score of 37 out of 100, ranking 489th of 2,219 in the study and 152nd of 574 in its sector. Its website passes 7 of 14 technical checks for AI tool readiness.

We asked 15 unbranded questions about its market, so no question mentioned Channel3 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
37Overall score
  • Visibility8
  • Citations1
  • Sentiment83
  • Site quality80
  • AI readiness50
Summary of account
Named by AI in
6.7%
4 of 60 answers
Share of mentions
12.1%
of the mentions of it and its 5 peers
AI readiness
7/14
technical checks passed. Typical for its sector: 4
Rank in its sector
152 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

Channel3 came up on 1 of 15 questions. Open any window to read that answer.

  1. 01How do usage-based fees work for AI shopping infrastructure platforms?0/4
  2. 02Typical pricing models for product discovery APIs in the US market0/4
  3. 03Why is product data quality important for accurate AI shopping recommendations?0/4
  4. 04Is an enterprise-grade product discovery API worth the investment for scaling retail applications?0/4
  5. 05What are the benefits of using a unified product catalog service for developing AI shopping solutions?0/4
  6. 06Alternatives to centralized product graph APIs for powering AI shopping solutions0/4
  7. 07How do developers enable real-time product discovery in AI shopping bots?0/4
  8. 08How can brands distribute their catalogs to emerging AI shopping platforms?0/4
  9. 09Options for small retailers to integrate with AI shopping ecosystems without building custom infrastructure0/4
  10. 10Ways to monetize product search through AI-driven shopping agents0/4
  11. 11Product graph API vs manual product data aggregation for e-commerce platforms0/4
  12. 12Top features to look for in AI shopping infrastructure solutions for US brands and developers0/4
  13. 13Integrated AI shopping infrastructure vs building from scratch: pros and cons0/4
  14. 14Common challenges when syncing large product catalogs with AI shopping APIs0/4
  15. 15Best AI-powered product graph APIs for powering shopping applications4/4
Total namedOpenAI: 1/15Claude: 1/15Perplexity: 1/15Gemini: 1/15All 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 Claude actually said

An answer that names the company

Claudenamed the company

“Best AI-powered product graph APIs for powering shopping applications”

I'll search for current information about the best AI-powered product graph APIs available for shopping applications.Based on recent information about AI-powered product APIs for shopping applications, here are the best options:

Top AI-Powered Product Graph APIs

1. Channel3

If you're building an AI shopping agent, Channel3 is the API to power it, with structured products, real prices, buy links, and built-in commission.

2. Shopify Catalog MCP

Shopify Catalog MCP shows the agent-facing discovery pattern clearly: search products, then fetch product details. Use it when agen …

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. Shopify API / Shopify Collective
    60.6%
  2. OpenAI Plugin Store (Shopping/Products APIs)
    27.3%
  3. Channel3
    12.1%
  4. Keepa API
    0.0%
  5. Algopix API
    0.0%
  6. Syndigo (Riversand API)
    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
    alhena.ai
    8
  2. 02
    datafiniti.co
    5
  3. 03
    algolia.com
    4
  4. 04
    shopify.com
    4
  5. 05
    cloud.google.com
    4
  6. 06
    github.com
    4
  7. 07
    stripe.com
    3
  8. 08
    ucphub.ai
    3
  9. 09
    dodopayments.com
    3
  10. 10
    docs.aws.amazon.com
    3

Channel3 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

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

How Channel3 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
8

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
83

How positively AI describes the company

Site quality
80

How well built the website's own pages are

AI readiness
50

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
37
Ranks 152 of 574. Typical company: 29
Named in answers
6.7%
Ranks 155 of 574. Typical company: 1.7%
AI readiness
50
Ranks 15 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
37
Ranks 63 of 315. Typical company: 28
Named in answers
6.7%
Ranks 66 of 315. Typical company: 1.7%
AI readiness
50
Ranks 10 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 4: Agent-integrated. At least one of an MCP card, A2A card, skills index or API catalog is published.

To reach level 5:
  • Web Bot Auth
  • 4 of MCP Server Card, A2A Agent Card, Agent Skills, API Catalog
  • 1 of OAuth discovery, OAuth Protected Resource, auth.md
Can an AI agent check out here?

Not by itself. Channel3 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 CardPublished
  • A2A Agent CardNot present
  • Agent SkillsNot present
  • API CatalogPublished
  • llms.txtPublished
  • 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 headersPassed

    HTTP Link headers on the homepage that point agents at machine readable resources.

    study: 1.5%
  • DNS for AI DiscoveryNot present

    Advertise agent endpoints with SVCB records under _agents.

    study: 4.3%
Content accessibility
100 of 100
  • Markdown negotiationPassed

    Requests sent with Accept: text/markdown receive a markdown version of the page.

    study: 6.2%
  • llms.txtPassed

    An llms.txt that tells language models what the site offers.

    study: 31.0%
Bot access control
68 of 100
  • AI bot rulesPartly met

    Add explicit robots.txt groups for the main AI crawlers.

    study: 92.7%
  • Content SignalsPassed

    Content-Signal lines in robots.txt declaring search, AI input and AI training preferences.

    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
40 of 100
  • API CatalogPassed

    A linkset at /.well-known/api-catalog listing APIs, specs and docs.

    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 CardPassed

    A server card describing the MCP server, its transport and capabilities.

    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 74 of 100 · 97% of checks could run · checked on October 9, 2026 · trychannel3.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

7 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

  • PassedMarkdown 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

  • PassedAPI 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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ShareSection 12

Share this result

Overall score 37 of 100 badge for Channel3

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/trychannel3.com"><img src="https://aeo-audit.rezolve.com/finance/badges/trychannel3.com.svg" alt="Overall score 37 of 100, Finance AI Visibility Study 2026" width="280" height="64"></a>
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