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Louisiana-Pacific

lpcorp.com · Industrial · LPX

Ranked 1,438 of 2,047 companies in the study

28Overall score
  • Visibility4
  • Citations1
  • Sentiment50
  • Site quality80
  • AI readiness29
What this means for Louisiana-Pacific

AI assistants rarely name Louisiana-Pacific, mentioning it in 1 of 60 answers. In that answer, James Hardie is also named. Its overall score is 28 out of 100, which ranks 1,438th of 2,047 companies and is below the typical company in its sector. The company's website passes 4 out of 14 technical checks for AI tool readiness.

We asked 15 unbranded questions about the industrial market: none named Louisiana-Pacific. AI assistants named it in 1 of 60 answers (1.7%). The typical industrial company is named in 5.0% of answers. By how often it is named, Louisiana-Pacific ranks 159 of 246 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.

Named by AI in
1.7%
1 of 60 answers
Share of mentions
7.1%
compared with 5 rivals
AI readiness
4/14
technical checks passed. Typical for its sector: 3
Rank in its sector
159 of 246
by overall score, where the typical industrial company scores 31
How Louisiana-Pacific 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
4

How often AI assistants name the company

Citations
1

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

Sentiment
50

How positively AI describes the company

Site quality
80

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 industrial

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

Overall score28
Ranks 159 of 246. Typical company: 31
Named in answers2%
Ranks 159 of 246. Typical company: 5%
AI readiness29
Ranks 34 of 246. Typical company: 21
What OpenAI actually said

An answer that names the company

“Where can contractors source advanced engineered wood materials for commercial projects in the US?”

Good question — for commercial work you’ll want both the right engineered-wood products (CLT, glulam, LVL, I‑joists, mass plywood panels, acetylated/thermally‑modified timber, etc.) and suppliers who can handle commercial volumes, design-assist, shop drawings and logistics. Below I’ve grouped the most useful sourcing channels, listed common national/regional manufacturers and specialty providers you’ll encounter, and included practical tips (specs, lead times, certifications and procurement steps). If you tell me the project location (state or ZIP) I can find nearby suppliers, current lead tim …

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

Also named
James Hardie3
Share of mentions

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

LP SmartSide (parented by LP, but competitors like TruWood Siding by Collins offer similar products)
55.6%
James Hardie
33.3%
Louisiana-Pacific
11.1%
Georgia-Pacific Building Products
0.0%
Nichiha USA
0.0%
Woodtone
0.0%
Which AI assistants named the company

Answers naming it, out of answers received

OpenAI
1/15
Gemini
0/15
Perplexity
0/15
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.lpcorp.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%
  • PassedHTTP 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
  • GPTBotallowed
  • ClaudeBotallowed
  • Anthropic-AIallowed
  • Google-Extendedallowed
  • Applebot-Extendedallowed
  • Meta-ExternalAgentallowed
  • FacebookBotallowed
  • Bytespiderallowed
  • CCBotallowed
  • Diffbotallowed
  • Omgilibotallowed
AI search
  • OAI-SearchBotallowed
  • Claude-SearchBotallowed
  • PerplexityBotallowed
  • Applebotallowed
  • Amazonbotallowed
  • YouBotallowed
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

apawood.org
18
modernize.com
16
justdial.com
14
angi.com
12
sherwoodlumber.com
7
allurausa.com
7
renoworks.com
6
lpcorp.com (its own website)
6
gvdrenovationsinc.com
6
homegeniusexteriors.com
6

In the study as US-listed.

Every question, and where the company came up (1 of 15)
QuestionOpenAIClaudePerplexityGemini
  • What common issues can occur with installed engineered wood siding and how can they be prevented?
  • Which siding materials are best for energy-efficient home construction?
  • How does the cost of engineered wood structural panels stack up against traditional lumber options?
  • What are the best engineered wood siding options for residential homes in the US?
  • How does oriented strand board compare to plywood for wall sheathing?
  • Is investing in premium engineered wood siding worth it for long-term home value?
  • How do you address moisture problems with engineered wood panels?
  • Which types of structural engineered wood panels are most recommended for commercial buildings?
  • What is the typical price range for engineered wood trim and siding per square foot in the US?
  • Engineered wood siding vs fiber cement: Which is better for durability and maintenance?
  • What are the most popular alternatives to engineered wood siding for exterior cladding?
  • Where can contractors source advanced engineered wood materials for commercial projects in the US?
  • Are engineered wood solutions suitable for high-humidity regions?
  • Do integrated building material systems simplify construction projects?
  • Eco-friendly substitutes for traditional engineered wood products in residential builds
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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