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

Named in

2of 60 answers

by 2 of 4 assistants

Statement note

What this means for Omnisient

AI assistants rarely name this market data company in their answers: they name it in 2 out of 60 answers, often naming Habu or InfoSum instead. Its overall score is 37 out of 100, ranking 517th of 2,219 companies. The website passes 4 out of 14 technical checks for AI tool readiness.

We asked 15 unbranded questions about its market, so no question mentioned Omnisient by name. AI assistants named it in 2 of the 60 answers. Counting only how often it is named, it ranks 223rd 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
37Overall score
  • Visibility6
  • Citations1
  • Sentiment100
  • Site quality80
  • AI readiness29
Summary of account
Named by AI in
3.3%
2 of 60 answers
Share of mentions
12.5%
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
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

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

  1. 01How can I resolve permission errors when setting up a secure data collaboration environment?0/4
  2. 02What are alternatives to privacy-preserving data collaboration platforms for secure B2B partnerships?0/4
  3. 03Which solutions help businesses collaborate on sensitive consumer data without compromising privacy?0/4
  4. 04What are common applications of privacy-focused data collaboration in healthcare and finance?0/4
  5. 05Are federated learning or clean rooms viable substitutes for privacy-preserving data collaboration software?0/4
  6. 06What are typical pricing models for enterprise-grade privacy-preserving data collaboration software in the US?0/4
  7. 07What should I consider before purchasing a data collaboration platform focused on privacy and compliance?0/4
  8. 08Why isn't my privacy-preserving data collaboration platform syncing data between partners?0/4
  9. 09Is investing in a privacy-preserving data collaboration platform worth it for a mid-sized enterprise?0/4
  10. 10Privacy-preserving data collaboration platforms vs traditional data sharing: what's the difference?0/4
  11. 11Are there pay-as-you-go options for privacy-first data sharing platforms for small businesses?0/4
  12. 12How can financial services companies use privacy-preserving technology to collaborate on customer analytics?0/4
  13. 13What are the best privacy-preserving data collaboration platforms for financial institutions in the US?2/4
  14. 14Which privacy technologies can businesses use instead of dedicated collaboration platforms for data protection?0/4
  15. 15How do secure data collaboration tools compare to encrypted file-sharing platforms for protecting consumer information?0/4
Total namedOpenAI: 0/15Claude: 1/15Perplexity: 1/15Gemini: 0/15All assistants: 2/60
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

“What are the best privacy-preserving data collaboration platforms for financial institutions in the US?”

… Omnisient: Omnisient's independent privacy-preserving data collaboration platform helps organizations generate new revenue, improve marketing performance, and manage risk by analyzing first-party data together without ever sharing it. The platform operates within an independent and neutral, ISO 27001-certified environment where data is never exchanged and personal information is never exposed, only insights.

Silence Laboratories: Silence's toolkit leverages advanced cryptographic techniques including MPC to enable secure collaboration on sensitive financial data, allowing multiple f …

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.

Also named

CompanyTimes named
  1. 01
    Habu
    4
  2. 02
    InfoSum
    4
  3. 03
    Privitar
    1
  4. 04
    TripleBlind
    1

Share of mentions

CompanyShare
  1. LiveRamp Safe Haven
    31.3%
  2. InfoSum
    25.0%
  3. Habu
    18.8%
  4. Omnisient
    12.5%
  5. TripleBlind
    6.3%
  6. Privitar
    6.3%
ReferrersSection 04

Websites the AI used as sources

How many times each website was listed as a source in these answers

  1. 01
    decentriq.com
    12
  2. 02
    expertinsights.com
    10
  3. 03
    arxiv.org
    9
  4. 04
    dualitytech.com
    8
  5. 05
    appsflyer.com
    8
  6. 06
    us.fitgap.com
    7
  7. 07
    aws.amazon.com
    7
  8. 08
    databricks.com
    6
  9. 09
    f6s.com
    5
  10. 10
    moldstud.com
    5

Omnisient is in the study as a market data company.

By assistantSection 05

Which AI assistants named the company

Answers naming it, out of answers received

Claude
1/15
Perplexity
1/15
Gemini
0/15
OpenAI
0/15
Market comparisonSection 06

How Omnisient 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
6

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
100

How positively AI describes the company

Site quality
80

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 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
3.3%
Ranks 223 of 574. Typical company: 1.7%
AI readiness
29
Ranks 224 of 574. Typical company: 29
Against its categorySection 08

Compared with market data companies

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

Overall score
37
Ranks 16 of 37. Typical company: 36
Named in answers
3.3%
Ranks 26 of 37. Typical company: 15.0%
AI readiness
29
Ranks 8 of 37. 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. Omnisient 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
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 negotiationNot met

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

    study: 6.2%
  • llms.txtPassed

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

    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 · omnisient.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%
  • Not metHTTP 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%
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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