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.
2,022 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 AgriCore

AI assistants do not name this fintech infrastructure company in any of their 60 answers to sector-related questions, while the typical company in its sector is named in 1.7% of answers. Its overall score is 23 out of 100, ranking 2,022nd of 2,219 companies in the study. Its website passes 1 of 14 technical checks for AI tool readiness.

We asked 15 unbranded questions about its market, so no question mentioned AgriCore 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
23Overall score
  • Visibility0
  • Citations0
  • Sentiment50
  • Site quality73
  • AI readiness7
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
1/14
technical checks passed. Typical for its sector: 4
Rank in its sector
539 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

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

  1. 01Options for US investors looking for sustainable agriculture opportunities outside of livestock digitization0/4
  2. 02How can a smallholder farmer use digital livestock platforms to increase profitability?0/4
  3. 03Common issues faced when registering land for digital livestock platforms0/4
  4. 04Are digital livestock platforms worth it for small-scale investors?0/4
  5. 05Capacity-building programs vs direct funding options for empowering smallholder farmers?0/4
  6. 06Ways agricultural investors can partner with digital livestock and capacity-building platforms0/4
  7. 07Is investing in digital livestock assets a good way to support sustainable agriculture?0/4
  8. 08How can rural communities benefit from digital livestock assets?0/4
  9. 09What are the best digital livestock platforms for smallholder farmers in the US?0/4
  10. 10Average cost to participate in digital livestock asset programs in the US0/4
  11. 11What are other ways to empower smallholder farmers besides digital asset platforms?0/4
  12. 12Alternatives to digital livestock assets for supporting rural agriculture0/4
  13. 13Do digital livestock platforms charge fees for capacity-building workshops?0/4
  14. 14What to do if you suspect fraudulent claims on a digital livestock asset platform?0/4
  15. 15Digital livestock investment services vs traditional livestock ownership — what's the difference?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

“How can a smallholder farmer use digital livestock platforms to increase profitability?”

Smallholder farmers can significantly increase their profitability by leveraging digital livestock platforms in several key ways:

1. Enhanced Market Access and Fairer Pricing

Direct Sales and Reduced Middlemen: Digital platforms connect farmers directly with buyers, including bulk purchasers and consumers, eliminating intermediaries. This allows farmers to secure better prices for their produce and retain a larger share of the profits.

Expanded Market Reach: Farmers can access a wider customer base beyond their local communities, including urban markets and even int …

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
    Farmcrowdy
    1
  2. 02
    ThriveAgric
    1
  3. 03
    Livestock Wealth
    1

Share of mentions

CompanyShare
  1. Farmcrowdy
    50.0%
  2. ThriveAgric
    33.3%
  3. Livestock Wealth
    16.7%
  4. AgriCore
    0.0%
  5. AgUnity
    0.0%
  6. Steadview Farms (Steadview Inc.)
    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
    livestockdata.org
    18
  2. 02
    cgspace.cgiar.org
    7
  3. 03
    farmkeep.com
    6
  4. 04
    sciencedirect.com
    6
  5. 05
    openknowledge.fao.org
    6
  6. 06
    documents1.worldbank.org
    6
  7. 07
    fao.org
    5
  8. 08
    frontiersin.org
    4
  9. 09
    mdpi.com
    4
  10. 10
    cftc.gov
    4

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

How AgriCore 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
7

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
23
Ranks 539 of 574. Typical company: 29
Named in answers
0.0%
Ranks 334 of 574. Typical company: 1.7%
AI readiness
7
Ranks 533 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
23
Ranks 289 of 315. Typical company: 28
Named in answers
0.0%
Ranks 168 of 315. Typical company: 1.7%
AI readiness
7
Ranks 293 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 0: Not yet agent-ready. Agents struggle to find basic information about the site.

To reach level 1:
  • 2 of robots.txt, Sitemap, Link headers
Can an AI agent check out here?

Not by itself. AgriCore 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
0 of 100
  • robots.txtNot met

    Publish a valid robots.txt with crawl rules and a Sitemap line.

    study: 86.1%
  • SitemapNot met

    Serve an XML sitemap and reference it 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
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
0 of 100
  • AI bot rulesNot 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 0 of 100 · 97% of checks could run · checked on October 9, 2026 · agricore.asia · 2,200 companies scanned

See how every company did, and how this was measured.

AI readinessSection 10

The checks behind the AI readiness score

1 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

  • Not metrobots.txt publishedstudy: 85.1%
  • Not metXML sitemapstudy: 79.4%
  • Not metHTTP 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%
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