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 and 10, 2026
when the AI assistants were asked
Account no.
1,498 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 Atomic.io

AI assistants do not name Atomic.io in any of their 60 answers to market questions, while companies such as Braze, OneSignal, and Airship are named instead. Its overall score is 26 out of 100, ranking 1,498th of 2,219 companies in the study. The website passes 5 of 14 technical checks measuring readiness for AI tools.

We asked 15 unbranded questions about its market, so no question mentioned Atomic.io 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
26Overall score
  • Visibility0
  • Citations0
  • Sentiment50
  • Site quality73
  • 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
418 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

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

  1. 01Best practices for using in-app messages to notify users about compliance updates?0/4
  2. 02Email versus in-app messaging for communicating product changes to users—what's more effective for medium to large businesses?0/4
  3. 03What are the most effective in-app messaging platforms for engaging mobile app users in the United States?0/4
  4. 04Best way to communicate urgent updates to customers directly within an app?0/4
  5. 05Is it worth investing in a dedicated in-app messaging platform for user engagement?0/4
  6. 06What should U.S. businesses look for when choosing their first in-app messaging solution?0/4
  7. 07Common issues when integrating an in-app messaging tool with a mobile application?0/4
  8. 08Alternatives to in-app messaging platforms for real-time customer communication in apps?0/4
  9. 09Typical pricing tiers for enterprise-level in-app messaging platforms?0/4
  10. 10Why are my app users not interacting with in-app messages as expected?0/4
  11. 11How much does it cost to implement an in-app communication platform for a medium-sized business in the U.S.?0/4
  12. 12How does in-app messaging compare to push notifications for user engagement?0/4
  13. 13Which in-app messaging platform features help increase customer trust and retention?0/4
  14. 14What are some lower-cost options for app user engagement besides in-app messages?0/4
  15. 15How can in-app messaging be used to onboard new users in a digital banking app?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 Gemini actually said

The company is not named in this answer

Geminidid not name the company

“What are the most effective in-app messaging platforms for engaging mobile app users in the United States?”

To effectively engage mobile app users in the United States, several in-app messaging platforms offer robust solutions with varying specializations. These platforms help businesses communicate directly with users while they are active in the app, which can significantly improve retention and brand loyalty.

Here are some of the most effective in-app messaging platforms:

For Comprehensive Engagement and Analytics:

Userpilot: Considered a top choice for both web and mobile apps, Userpilot provides a no-code platform for product managers and customer success teams to create in-app ex …

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
    Braze
    8
  2. 02
    OneSignal
    8
  3. 03
    Airship
    4
  4. 04
    Iterable
    4

Share of mentions

CompanyShare
  1. OneSignal
    26.7%
  2. Braze
    26.7%
  3. Leanplum (now CleverTap Engage)
    20.0%
  4. Airship
    13.3%
  5. Iterable
    13.3%
  6. Atomic.io
    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
    userpilot.com
    19
  2. 02
    knock.app
    15
  3. 03
    moengage.com
    11
  4. 04
    businessofapps.com
    10
  5. 05
    pushwoosh.com
    9
  6. 06
    customer.io
    9
  7. 07
    appcues.com
    9
  8. 08
    clevertap.com
    8
  9. 09
    chameleon.io
    8
  10. 10
    sendbird.com
    7

Atomic.io 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

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

How Atomic.io 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
73

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
26
Ranks 418 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 fintech infrastructure companies

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

Overall score
26
Ranks 220 of 315. Typical company: 28
Named in answers
0.0%
Ranks 168 of 315. Typical company: 1.7%
AI readiness
36
Ranks 40 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 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. Atomic.io 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
50 of 100
  • Markdown negotiationPassed

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

    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 36 of 100 · 97% of checks could run · checked on October 9, 2026 · atomic.io · 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

  • PassedMarkdown 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

  • GPTBotallowed
  • ClaudeBotallowed
  • Anthropic-AIallowed
  • Google-Extendedallowed
  • Applebot-Extendedallowed
  • Meta-ExternalAgentallowed
  • FacebookBotallowed
  • Bytespiderallowed
  • CCBotallowed
  • Diffbotallowed
  • Omgilibotallowed

AI search

  • OAI-SearchBotallowed
  • Claude-SearchBotallowed
  • PerplexityBotallowed
  • Applebotallowed
  • Amazonbotallowed
  • YouBotallowed

Answering questions

  • ChatGPT-Userallowed
  • Claude-Userallowed
  • Perplexity-Userallowed
  • DuckAssistBotallowed
  • MistralAI-Userallowed

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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