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Orion Office REIT

onlreit.com · Finance · ONL

Ranked 1,249 of 2,047 companies in the study

30Overall score
  • Visibility9
  • Citations1
  • Sentiment57
  • Site quality80
  • AI readiness21
What this means for Orion Office REIT

AI assistants rarely name Orion Office REIT. The company appears in just 2 answers out of 60, sometimes alongside Easterly Government Properties and Piedmont Office Realty Trust. Its overall score is 30 out of 100, ranking 1,249th of 2,047, about the same as the typical company in its sector. The website passes 3 of 14 technical checks for AI tool readiness.

We asked 15 unbranded questions about the finance market: none named Orion Office REIT. AI assistants named it in 2 of 60 answers (3.3%). The typical finance company is named in 3.3% of answers. By how often it is named, Orion Office REIT ranks 87 of 205 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
3.3%
2 of 60 answers
Share of mentions
18.2%
compared with 5 rivals
AI readiness
3/14
technical checks passed. Typical for its sector: 3
Rank in its sector
80 of 205
by overall score, where the typical finance company scores 29
How Orion Office REIT 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
9

How often AI assistants name the company

Citations
1

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

Sentiment
57

How positively AI describes the company

Site quality
80

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 finance

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

Overall score30
Ranks 80 of 205. Typical company: 29
Named in answers3%
Ranks 87 of 205. Typical company: 3%
AI readiness21
Ranks 82 of 205. Typical company: 21
What Perplexity actually said

An answer that names the company

“Who typically invests in U.S. suburban net lease office real estate?”

Typical buyers of U.S. suburban net lease office assets are private investors, institutional investors, equity funds, REITs, and sometimes cross-border/international capital. CBRE’s 2025 net lease data says private buyers were the most active participants, while institutional investors and equity funds and REITs were also meaningful sources of capital.

For this specific property type, the buyer pool is often narrower and more specialized: firms like Sentinel Net Lease and Orion focus on single-tenant, mission-critical suburban office buildings with long-term …

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

Also named
Easterly Government Properties2Piedmont Office Realty Trust1
Share of mentions

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

Easterly Government Properties
50.0%
Orion Office REIT
33.3%
Piedmont Office Realty Trust
16.7%
VEREIT Office Properties (part of American Finance Trust, Inc.)
0.0%
Office Properties Income Trust (OPI)
0.0%
City Office REIT
0.0%
Which AI assistants named the company

Answers naming it, out of answers received

Perplexity
2/15
Claude
0/15
Gemini
0/15
OpenAI
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 0: Not yet agent-ready. Agents struggle to find basic information about the site.

To reach level 1:
  • 2 of robots.txt, Sitemap, Link headers
Show every check, for your technical team
Discoverability
31 of 100
  • robots.txtNot met

    Publish a valid robots.txt with crawl rules and a Sitemap line.

    study: 92.0%
  • SitemapPartly met

    Serve an XML sitemap and reference it 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
0 of 100
  • AI bot rulesNot 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 7 of 100 · 97% of checks could run · checked on October 5, 2026 · www.onlreit.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

cbre.com
28
d1io3yog0oux5.cloudfront.net
21
sentinelnetlease.com
16
trepp.com
13
cushmanwakefield.com
13
assets.cushmanwakefield.com
12
umbrex.com
12
pwc.com
11
avisonyoung.us
11
northmarq.com
10

In the study as US-listed.

Every question, and where the company came up (2 of 15)
QuestionOpenAIClaudePerplexityGemini
  • Which U.S. markets are currently strongest for net lease suburban office investment?
  • Alternatives to investing directly in suburban office buildings on a net lease basis
  • Is it a good time to invest in net lease suburban office real estate given current market trends?
  • How are management fees structured for institutional investment in net lease office portfolios?
  • Net lease vs gross lease structures for suburban office properties—what are the main differences for investors?
  • How can investors manage tenant default risk in net lease suburban office investments?
  • What are common challenges with leasing suburban office buildings on a net lease basis?
  • How do net lease suburban office portfolios help diversify commercial property investments?
  • Are suburban single-tenant office portfolios worth considering for long-term investment?
  • How do suburban net lease office assets compare to downtown office buildings in terms of stability and returns?
  • Who typically invests in U.S. suburban net lease office real estate?
  • What affects the yield and cap rates for suburban net lease office properties in the U.S.?
  • What are the main alternatives to suburban net lease office REITs for income-focused investors?
  • What are the best ways to invest in suburban net lease office real estate in the U.S.?
  • Top factors to consider when selecting a net lease office portfolio in suburban markets
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.

Next step

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