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Fair Isaac

fico.com · Technology · FICO

Ranked 919 of 2,047 companies in the study

34Overall score
  • Visibility13
  • Citations1
  • Sentiment67
  • Site quality87
  • AI readiness21
What this means for Fair Isaac

AI assistants name Fair Isaac in 6.7% of answers, which is less often than the typical company in the technology sector. Its overall score is 34 out of 100, ranking 919th of 2,047 companies. The website passes 3 of 14 technical checks for how ready it is for AI tools.

We asked 15 unbranded questions about the technology market: none named Fair Isaac. AI assistants named it in 4 of 60 answers (6.7%). The typical technology company is named in 10.0% of answers. By how often it is named, Fair Isaac ranks 165 of 273 in its sector.

Named by AI in
6.7%
4 of 60 answers
Share of mentions
22.2%
compared with 5 rivals
AI readiness
3/14
technical checks passed. Typical for its sector: 4
Rank in its sector
157 of 273
by overall score, where the typical technology company scores 36
How Fair Isaac compares with all 2,047 companies

Every dot is a company in the study. Hover one to see it; click to open its report.

This companySame sectorEvery other companyNever named

What makes up the score

Five parts, each scored out of 100.

Visibility
13

How often AI assistants name the company

Citations
1

How often AI uses the company's own website as a source

Sentiment
67

How positively AI describes the company

Site quality
87

How well built the website's own pages are

AI readiness
21

How easily AI tools can read and use the website

Visibility is calculated from the answers on this page. How the score is built.

Compared with technology

273 companies in this sector. The line on each bar is the typical company.

Overall score34
Ranks 157 of 273. Typical company: 36
Named in answers7%
Ranks 165 of 273. Typical company: 10%
AI readiness21
Ranks 161 of 273. Typical company: 29
What OpenAI actually said

An answer that names the company

“What are the top analytics and decision intelligence platforms for improving customer understanding?”

Below is a concise, practical list of the leading types of platforms and the specific vendors you should evaluate when your goal is “improving customer understanding” — i.e., building unified customer profiles, surfacing why customers behave the way they do, deciding what action to take, and automating/operationalizing those actions.

Summary (by capability)

Product & digital analytics (behavioral measurement + product/UX insight)

Amplitude — product analytics, behavioral cohorts, path and funnel analysis (strong for product-led teams).

Mixpanel — event-based analytics, retention ana …

The AI’s answer as we received it, shortened and not checked for accuracy.

Also named
SAS5FICO3
Share of mentions

How the mentions in these answers were split between this company and its rivals

SAS
61.5%
Fair Isaac
30.8%
Oracle Analytics Cloud
7.7%
IBM Decision Optimization (IBM Cloud Pak for Data)
0.0%
Experian Decision Analytics
0.0%
SAS Decision Manager
0.0%
Which AI assistants named the company

Answers naming it, out of answers received

OpenAI
2/15
Gemini
1/15
Perplexity
1/15
Claude
0/15
Ready for AI agents

What this website publishes for an AI agent to read, use and buy from, 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
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: 92.0%
  • SitemapPassed

    An XML sitemap listing the pages, ideally referenced from robots.txt.

    study: 86.8%
  • Link headersNot met

    Send Link headers such as rel="api-catalog" or rel="describedby" on the homepage.

    study: 0.3%
  • DNS for AI DiscoveryNot present

    Advertise agent endpoints with SVCB records under _agents.

    study: 5.5%
Content accessibility
0 of 100
  • Markdown negotiationNot met

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

    study: 1.9%
  • llms.txtNot met

    Publish an llms.txt with a short summary and the key links.

    study: 25.1%
Bot access control
32 of 100
  • AI bot rulesPartly met

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

    study: 93.4%
  • Content SignalsNot met

    Add a Content-Signal line for search, ai-input and ai-train to robots.txt.

    study: 1.4%
  • Web Bot AuthNot present

    Only relevant if you run your own agents or crawlers: publish a signing key directory.

    study: 0.2%
APIs, auth and MCP
0 of 100
  • API CatalogNot met

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

    study: 0.3%
  • OAuth discoveryNot met

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

    study: 11.8%
  • OAuth Protected ResourceNot met

    Serve protected resource metadata at /.well-known/oauth-protected-resource.

    study: 10.3%
  • auth.mdNot met

    Publish an auth.md describing how agents sign in.

    study: 0.0%
  • MCP Server CardNot met

    Offer an MCP server and publish its server card under /.well-known.

    study: 0.2%
  • A2A Agent CardNot met

    Publish an agent card at /.well-known/agent-card.json.

    study: 0.1%
  • Agent SkillsNot met

    Publish a skills index with the main tasks agents can do.

    study: 0.2%
  • WebMCPCould not check

    Register key actions such as search or cart as WebMCP tools.

    study: 33.7%
  • ARD manifestNot met

    Publish an ai-catalog.json listing every agent interface.

    study: 0.1%

Score 25 of 100 · 97% of checks could run · checked on October 5, 2026 · www.fico.com · 2,047 companies scanned

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

The checks behind the AI readiness score

3 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: 85.0%
  • PassedXML sitemapstudy: 73.2%
  • Not metHTTP Link headers (RFC 8288)study: 29.0%
Content Accessibility
  • Not metMarkdown content negotiationstudy: 8.3%
  • Not metllms.txt publishedstudy: 21.7%
  • PassedToken budget (page weight)study: 95.2%
Bot Access Control
  • Not metExplicit AI bot rulesstudy: 13.0%
API / Auth / MCP
  • Not metAPI Catalog (.well-known/api-catalog)study: 0.2%
  • Not metOAuth Authorization Server discoverystudy: 10.1%
  • Not metOAuth Protected Resource discoverystudy: 9.3%
  • Not metMCP Server Cardstudy: 0.0%
  • Not metA2A Agent Cardstudy: 0.0%
  • Not metWebMCP toolsstudy: 4.2%
  • Not metAgent Skills declaredstudy: 0.0%
What AI crawlers may read (robots.txt)

This website sets no rules for any AI crawler by name, like 84% 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.

Websites the AI used as sources

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

domo.com
21
ibm.com
17
thoughtspot.com
8
getdot.ai
8
linkurious.com
8
cxtoday.com
7
dataiku.com
7
gartner.com
7
sas.com
7
teradata.com
6

In the study as S&P 500.

Every question, and where the company came up (2 of 15)
QuestionOpenAIClaudePerplexityGemini
  • Is investing in advanced decision intelligence software worth it for mid-sized businesses?
  • What is the difference between decision intelligence platforms and predictive analytics tools?
  • Why might an analytics platform return inaccurate customer insights?
  • What are some good alternatives to enterprise-level decision intelligence platforms for small businesses?
  • Emerging trends in applied intelligence for customer engagement across industries?
  • How can decision intelligence platforms help improve customer retention for financial services?
  • How much does it typically cost to deploy an end-to-end decision intelligence solution for a medium-sized business?
  • How do analytics software and traditional business intelligence tools compare?
  • Best analytics approaches for personalizing retail customer experiences?
  • Open source options for advanced analytics and automated decision-making software?
  • What are the top analytics and decision intelligence platforms for improving customer understanding?
  • Common challenges when integrating decision intelligence software with existing business systems?
  • Best decision intelligence solutions for optimizing business processes in large organizations?
  • Should organizations prioritize analytics solutions with real-time decisioning capabilities?
  • What factors influence the pricing of enterprise analytics and decisioning software in the US?
named the companyanswered without naming itdid not answer

Columns, left to right: OpenAI, Claude, Perplexity, Gemini. The AI assistants often disagree. Across the study, on 40% of the questions where a company is named, only one of the four names it.

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