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
Rezolve Ai
MethodDemo
Back to the study
AI visibility statementFinance AI Visibility Study 2026Issued October 14, 2026
Account holder

TigerGraph

tigergraph.com

Banking and fintech infrastructureFinancial technology and data

Money20/20 attendee

Statement period
October 9 to 14, 2026
when the AI assistants were asked
Account no.
15 of 2,219
its rank by overall score
Place in its category
4th of 315 fintech infrastructure companies
Closing balance

Named in

25of 60 answers

by 4 of 4 assistants

Statement note

What this means for TigerGraph

AI assistants name this fintech infrastructure company in 41.7% of answers, while the typical company in its sector is named in 1.7% of answers. TigerGraph's overall score is 48 out of 100, ranking 15th of 2,219 companies and 6th 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 TigerGraph by name. AI assistants named it in 25 of the 60 answers. Counting only how often it is named, it ranks 8th of 574 in its sector. The typical financial technology and data company is named in 1.7% of answers.

Overall score
48Overall score
  • Visibility35
  • Citations1
  • Sentiment87
  • Site quality87
  • AI readiness50
Summary of account
Named by AI in
41.7%
25 of 60 answers
Share of mentions
27.2%
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
6 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

TigerGraph came up on 13 of 15 questions. Open any window to read that answer.

  1. 01What are the best graph databases for large-scale fraud detection in financial services?4/4
  2. 02Which enterprise graph database solutions work well for regulatory compliance analytics?4/4
  3. 03Common causes of failed relationship traversal in a graph database during analytics workloads1/4
  4. 04Are enterprise graph databases good for organizations needing sub-100ms query performance?0/4
  5. 05How are graph databases used to uncover hidden connections in cybersecurity threat detection?2/4
  6. 06What is the process of using a graph database for entity resolution in healthcare or insurance?1/4
  7. 07Why is my graph database query performance slow on massive datasets?1/4
  8. 08How does a property graph database compare to a labeled graph database for entity resolution tasks?1/4
  9. 09Difference between native and non-native graph databases for real-time analytics0/4
  10. 10Top graph databases for supporting AI-driven customer 360 platforms4/4
  11. 11Alternatives to real-time graph databases for uncovering complex relationships in big data analytics1/4
  12. 12Does a graph database make sense for regulatory reporting in highly regulated industries?1/4
  13. 13Is investing in an enterprise graph database worth it for real-time supply chain visibility?1/4
  14. 14Graph database vs. relational database for anti-money laundering use cases1/4
  15. 15What is the typical pricing for an enterprise-level graph database with petabyte-scale capabilities?3/4
Total namedOpenAI: 11/15Claude: 4/15Perplexity: 4/15Gemini: 6/15All assistants: 25/60
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 Perplexity actually said

An answer that names the company

Perplexitynamed the company

“Top graph databases for supporting AI-driven customer 360 platforms”

For an AI-driven Customer 360 platform, the strongest shortlist is Neo4j, TigerGraph, Amazon Neptune, Stardog, and ArangoDB. Add Azure Cosmos DB for Microsoft-centric environments, or PuppyGraph when querying existing relational data with minimal migration is the priority. The best choice depends on whether the platform emphasizes operational identity resolution, real-time multi-hop analytics, semantic knowledge graphs, or cloud integration.

Recommended shortlist

Database · Best fit · Strengths · Watch-outs

Neo4j · General-purpose Customer 360 a …

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
    Neo4j
    30
  2. 02
    ArangoDB
    15
  3. 03
    Amazon Neptune
    15
  4. 04
    OrientDB
    1

Share of mentions

CompanyShare
  1. Neo4j
    35.9%
  2. TigerGraph
    27.2%
  3. Amazon Neptune
    20.7%
  4. ArangoDB
    13.0%
  5. Microsoft Azure Cosmos DB (Graph API)
    2.2%
  6. OrientDB
    1.1%
ReferrersSection 04

Websites the AI used as sources

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

  1. 01
    tigergraph.com (its own website)
    59
  2. 02
    neo4j.com
    24
  3. 03
    puppygraph.com
    17
  4. 04
    memgraph.com
    9
  5. 05
    hydradb.com
    8
  6. 06
    arxiv.org
    7
  7. 07
    falkordb.com
    7
  8. 08
    aws.amazon.com
    5
  9. 09
    go.neo4j.com
    4
  10. 10
    services.google.com
    4

TigerGraph 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

OpenAI
11/15
Gemini
6/15
Claude
4/15
Perplexity
4/15
Market comparisonSection 06

How TigerGraph 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
35

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
87

How positively AI describes the company

Site quality
87

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
48
Ranks 6 of 574. Typical company: 29
Named in answers
41.7%
Ranks 8 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
48
Ranks 4 of 315. Typical company: 28
Named in answers
41.7%
Ranks 2 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 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. TigerGraph 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
63 of 100
  • AI bot rulesPassed

    Explicit robots.txt rules for AI crawlers such as GPTBot, ClaudeBot and PerplexityBot.

    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
18 of 100
  • API CatalogNot met

    List public APIs in a linkset at /.well-known/api-catalog.

    study: 1.3%
  • OAuth discoveryPartly met

    Publish OpenID Connect or OAuth server metadata under /.well-known.

    study: 6.3%
  • OAuth Protected ResourcePassed

    Metadata telling agents which authorization server to use.

    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 49 of 100 · 97% of checks could run · checked on October 9, 2026 · www.tigergraph.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%
  • 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

  • PassedExplicit AI bot rulesstudy: 11.5%

API / Auth / MCP

  • Not metAPI Catalog (.well-known/api-catalog)study: 1.1%
  • PassedOAuth Authorization Server discoverystudy: 5.2%
  • PassedOAuth 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 rules for 1 AI crawler by name. All others follow its general rules.

Training AI

  • GPTBotallowed
  • ClaudeBotallowed
  • Anthropic-AIallowed
  • Google-Extendedallowed
  • Applebot-Extendedallowed
  • Meta-ExternalAgentallowed
  • FacebookBotallowed
  • Bytespider*blocked
  • 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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ShareSection 12

Share this result

Overall score 48 of 100 badge for TigerGraph

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/tigergraph.com"><img src="https://aeo-audit.rezolve.com/finance/badges/tigergraph.com.svg" alt="Overall score 48 of 100, Finance AI Visibility Study 2026" width="280" height="64"></a>
End of statement
All 2,219 companiesHow we measured this
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