- Visibility23
- Citations1
- Sentiment50
- Site quality73
- AI readiness36
AI assistants name Huntington Ingalls Industries in 16.7% of answers, which is more frequent than the typical company in its sector at 5%. Its overall score is 33 out of 100, ranking 951st of 2,047 companies. The website passes 5 of 14 technical checks for AI tool readiness.
We asked 15 unbranded questions about the industrial market: none named Huntington Ingalls Industries. AI assistants named it in 10 of 60 answers (16.7%). The typical industrial company is named in 5.0% of answers. By how often it is named, Huntington Ingalls Industries ranks 42 of 246 in its sector.
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.
246 companies in this sector. The line on each bar is the typical company.
An answer that names the company
“Which companies offer cutting-edge unmanned maritime systems for defense?”
Several companies are widely cited as offering cutting-edge unmanned maritime systems for defense, especially in USVs (unmanned surface vehicles) and UUVs/AUVs (unmanned underwater/autonomous underwater vehicles). Examples include L3Harris, Lockheed Martin, Hanwha Systems, Elbit Systems, HII, Exail, Teledyne Marine, Fincantieri, Kraken Robotics, Oceaneering International, and Sea Machines Robotics.
A concise view of notable defense-focused suppliers:
L3Harris — offers autonomous surface and unde …
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 DiscoveryPassed
SVCB or HTTPS records under _agents that advertise agent endpoints.
- 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.txtPassed
An llms.txt that tells language models what the site offers.
- study: 93.4%AI bot rulesPassed
Explicit robots.txt rules for AI crawlers such as GPTBot, ClaudeBot and PerplexityBot.
- 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 45 of 100 · 97% of checks could run · checked on October 5, 2026 · www.hii.com · 2,047 companies scanned
5 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%
- Passedllms.txt publishedstudy: 21.7%
- PassedToken budget (page weight)study: 95.2%
- PassedExplicit 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 rules for 10 AI crawlers by name. All others follow its general rules.
- GPTBot*allowed
- ClaudeBot*allowed
- Anthropic-AI*allowed
- Google-Extended*allowed
- Applebot-Extended*allowed
- Meta-ExternalAgentpartly
- FacebookBot*allowed
- Bytespiderpartly
- CCBotpartly
- Diffbotpartly
- Omgilibotpartly
- OAI-SearchBot*allowed
- Claude-SearchBotpartly
- PerplexityBot*allowed
- Applebotpartly
- Amazonbotpartly
- YouBot*allowed
- ChatGPT-User*allowed
- 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 S&P 500.
- Which companies offer cutting-edge unmanned maritime systems for defense?
- Are there U.S.-based solutions for autonomous surface and undersea systems aside from traditional shipyards?
- How is budgeting for integrated mission technologies in naval shipbuilding typically structured?
- How do nuclear-powered vs conventionally-powered naval ships compare in terms of operational range and cost?
- What options exist for upgrading legacy vessels with the latest mission technology without full replacement?
- How are nuclear infrastructure services applied in modern naval fleet operations?
- What are common issues faced when deploying unmanned undersea systems in navy missions?
- What are the best shipbuilders in the U.S. for advanced naval vessels?
- What are the main differences between U.S. Navy destroyers and frigates in terms of capabilities and roles?
- What are the key mission applications for all-domain maritime technology in national security?
- Is investing in new mission technologies for naval fleets worth the cost for national defense needs?
- What factors influence the cost of constructing advanced surface combatants in the U.S.?
- Do all-domain solutions add significant value to U.S. naval operations?
- How can challenges in integrating autonomous platforms into existing fleets be addressed?
- What are alternatives to manned platforms for maritime surveillance and reconnaissance?
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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<a href="https://aeo-audit.rezolve.com/us/hii.com"><img src="https://aeo-audit.rezolve.com/us/badges/hii.com.svg" alt="Overall score 33 of 100, US AI Visibility Study 2026" width="280" height="64"></a>