- Visibility5
- Citations1
- Sentiment100
- Site quality87
- AI readiness21
AI assistants rarely name C3.ai, mentioning it in 2 of 60 answers. For comparison, the typical company in the technology sector is named in 10% of answers. Its overall score is 38 out of 100, ranking 598th of 2,047 companies. The company's website passes 3 of 14 technical checks for AI tool readiness.
We asked 15 unbranded questions about the technology market: none named C3.ai. AI assistants named it in 2 of 60 answers (3.3%). The typical technology company is named in 10.0% of answers. By how often it is named, C3.ai ranks 200 of 273 in its sector.
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 rivals.
Every dot is a company in the study. Hover one to see it; click to open its report.
This companySame sectorEvery other companyNever named
Five parts, each scored out of 100.
How often AI assistants name the company
How often AI uses the company's own website as a source
How positively AI describes the company
How well built the website's own pages are
How easily AI tools can read and use the website
Visibility is calculated from the answers on this page. How the score is built.
273 companies in this sector. The line on each bar is the typical company.
An answer that names the company
“What are the best enterprise AI software platforms for optimizing industrial operations?”
I'll search for current information on enterprise AI platforms designed for industrial operations.Based on current information, here are the best enterprise AI software platforms for optimizing industrial operations:
Leading Industrial AI Platforms
The leading Industrial AI platforms for large enterprises in 2026 are IFS.ai, Cognite, AVEVA, Siemens Insights Hub, Honeywell Forge, GE Vernova, Rockwell Automation FactoryTalk Analytics, Hexagon, PTC ThingWorx, and ABB Ability.
Today's leading platforms combine artificial intelligence with enterprise applications, operational technology (OT), …
The AI’s answer as we received it, shortened and not checked for accuracy.
How the mentions in these answers were split between this company and its rivals
Answers naming it, out of answers received
What this website publishes for an AI agent to read, use and buy from, on a scale of six levels.
- 0
- 1
- 2
- 3
- 4
- 5
Level 1: Basic web presence. Two of robots.txt, a sitemap and Link headers are in place.
- Content Signals
Show every check, for your technical teamHide the checks
- study: 92.0%robots.txtPassed
A valid robots.txt with crawl rules at the site root.
- study: 86.8%SitemapPassed
An XML sitemap listing the pages, ideally referenced from robots.txt.
- study: 0.3%Link headersNot met
Send Link headers such as rel="api-catalog" or rel="describedby" on the homepage.
- study: 5.5%DNS for AI DiscoveryNot present
Advertise agent endpoints with SVCB records under _agents.
- study: 1.9%Markdown negotiationNot met
Return a markdown version when asked with Accept: text/markdown, for example at the CDN.
- study: 25.1%llms.txtNot met
Publish an llms.txt with a short summary and the key links.
- study: 93.4%AI bot rulesPartly met
Add explicit robots.txt groups for the main AI crawlers.
- study: 1.4%Content SignalsNot met
Add a Content-Signal line for search, ai-input and ai-train to robots.txt.
- study: 0.2%Web Bot AuthNot present
Only relevant if you run your own agents or crawlers: publish a signing key directory.
- study: 0.3%API CatalogNot met
List public APIs in a linkset at /.well-known/api-catalog.
- study: 11.8%OAuth discoveryNot met
Publish OpenID Connect or OAuth server metadata under /.well-known.
- study: 10.3%OAuth Protected ResourceNot met
Serve protected resource metadata at /.well-known/oauth-protected-resource.
- study: 0.0%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: 0.1%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: 33.7%WebMCPCould not check
Register key actions such as search or cart as WebMCP tools.
- study: 0.1%ARD manifestNot met
Publish an ai-catalog.json listing every agent interface.
Score 25 of 100 · 97% of checks could run · checked on October 5, 2026 · c3.ai · 2,047 companies scanned
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 checksHide them
- Passedrobots.txt publishedstudy: 85.0%
- PassedXML sitemapstudy: 73.2%
- Not metHTTP Link headers (RFC 8288)study: 29.0%
- Not metMarkdown content negotiationstudy: 8.3%
- Not metllms.txt publishedstudy: 21.7%
- PassedToken budget (page weight)study: 95.2%
- Not metExplicit AI bot rulesstudy: 13.0%
- 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%
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.
- GPTBotpartly
- ClaudeBotpartly
- Anthropic-AIpartly
- Google-Extendedpartly
- Applebot-Extendedpartly
- Meta-ExternalAgentpartly
- FacebookBotpartly
- Bytespiderpartly
- CCBotpartly
- Diffbotpartly
- Omgilibotpartly
- OAI-SearchBotpartly
- Claude-SearchBotpartly
- PerplexityBotpartly
- Applebotpartly
- Amazonbotpartly
- YouBotpartly
- 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.
How many times each website was listed as a source in these answers
In the study as US-listed.
- Why isn’t my enterprise AI application delivering the expected operational improvements?
- Alternatives to enterprise AI platforms for organizations seeking digital transformation solutions
- What are the best enterprise AI software platforms for optimizing industrial operations?
- Enterprise AI platforms vs cloud-based machine learning platforms—what are the key differences?
- Which AI solutions are most effective for mission-critical reliability in utilities and energy sectors?
- How do AI application platforms compare to traditional process automation tools for enterprises?
- What non-AI tools can be used to optimize decision-making and process automation at scale?
- Common challenges when integrating AI workflow automation platforms into manufacturing environments
- What should government agencies look for when evaluating advanced AI software suites?
- Which AI-driven solutions help large organizations automate decision-making processes?
- Is investing in an enterprise AI software platform worth it for large corporations?
- How can AI platforms improve demand forecasting and supply chain efficiency in large enterprises?
- What are practical uses for agentic AI systems in government operations?
- Do most industrial AI application suites offer tiered pricing based on scale or features?
- How are enterprise AI software platforms typically priced for large organizations in the US?
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.