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Appian

appian.com · Technology · APPN

Ranked 310 of 2,047 companies in the study

41Overall score
  • Visibility23
  • Citations2
  • Sentiment81
  • Site quality87
  • AI readiness29
What this means for Appian

AI assistants name Appian in 21.7% of answers, which is more than twice as often as the typical company in its sector. Appian has an overall score of 41 out of 100, ranking 310th of 2,047 companies. Its website passes 4 of 14 technical checks for AI tool readiness.

We asked 15 unbranded questions about the technology market: none named Appian. AI assistants named it in 13 of 60 answers (21.7%). The typical technology company is named in 10.0% of answers. By how often it is named, Appian ranks 77 of 273 in its sector.

Named by AI in
21.7%
13 of 60 answers
Share of mentions
25.5%
compared with 5 rivals
AI readiness
4/14
technical checks passed. Typical for its sector: 4
Rank in its sector
57 of 273
by overall score, where the typical technology company scores 36
How Appian 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
23

How often AI assistants name the company

Citations
2

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

Sentiment
81

How positively AI describes the company

Site quality
87

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.

Compared with technology

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

Overall score41
Ranks 57 of 273. Typical company: 36
Named in answers22%
Ranks 77 of 273. Typical company: 10%
AI readiness29
Ranks 82 of 273. Typical company: 29
What Gemini actually said

An answer that names the company

“What are the top AI-powered enterprise process orchestration platforms for large organizations?”

For large organizations seeking to implement AI-powered enterprise process orchestration, several platforms stand out for their ability to design, orchestrate, and manage AI-powered workflows across multiple systems with a focus on scalability, governance, and security. These platforms move beyond simple task automation to enable the creation of AI agents that can reason, retrieve data, and act autonomously within enterprise guidelines.

Here are some of the top AI-powered enterprise process orchestration platforms for large organizations:

Cloud-Native and Integrated Platforms:

Micr …

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

Also named
UiPath17ServiceNow9Nintex1Pegasystems1
Share of mentions

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

UiPath
39.1%
Appian
28.3%
ServiceNow
26.1%
Pegasystems
4.3%
Nintex
2.2%
Kofax
0.0%
Which AI assistants named the company

Answers naming it, out of answers received

Gemini
5/15
Perplexity
4/15
Claude
2/15
OpenAI
2/15
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%
  • WebMCPNot met

    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 24 of 100 · 100% of checks could run · checked on October 3, 2026 · appian.com · 2,047 companies scanned

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

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: 85.0%
  • 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
  • PassedExplicit 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 rules for 3 AI crawlers by name. All others follow its general rules.

Training AI
  • GPTBotallowed
  • ClaudeBotallowed
  • Anthropic-AIallowed
  • Google-Extendedallowed
  • Applebot-Extendedallowed
  • Meta-ExternalAgentallowed
  • FacebookBotallowed
  • Bytespiderallowed
  • CCBot*blocked
  • Diffbotallowed
  • Omgilibot*blocked
AI search
  • OAI-SearchBotallowed
  • Claude-SearchBotallowed
  • PerplexityBotallowed
  • Applebotallowed
  • Amazonbotallowed
  • YouBot*blocked
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.

Websites the AI used as sources

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

ibm.com
19
techtarget.com
18
elementum.ai
16
moveworks.com
15
vellum.ai
13
domo.com
12
appian.com (its own website)
10
moxo.com
9
zapier.com
8
kestra.io
8

In the study as US-listed.

Every question, and where the company came up (5 of 15)
QuestionOpenAIClaudePerplexityGemini
  • How does AI-powered process orchestration compare to traditional workflow automation tools?
  • What options are available for organizations needing to automate processes without disrupting existing IT infrastructure?
  • What are common use-cases for AI-powered platforms in finance operations automation?
  • What are the top AI-powered enterprise process orchestration platforms for large organizations?
  • What factors affect the pricing of enterprise AI process automation platforms?
  • What alternatives exist to AI-driven process orchestration for automating business operations?
  • Best enterprise platforms for orchestrating people, systems, and AI agents across critical business workflows
  • Are there affordable options for AI-powered workflow automation for large organizations?
  • Which automation platforms can help modernize critical business processes without replacing existing IT systems?
  • How can process orchestration platforms help streamline supply chain operations in a large organization?
  • What should I consider before choosing an enterprise platform for AI-based process automation?
  • Is investing in an AI-powered business process automation platform worth it for large enterprises?
  • Why isn't my process orchestration platform integrating smoothly with legacy business systems?
  • What are the differences between low-code automation platforms and fully AI-driven process orchestration solutions?
  • What can cause AI automation workflows to fail in enterprise environments?
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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Overall score 41 of 100 badge for Appian

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