AI visibility score
4.2/ 10Fair

#859,782 of 2,705,698 in Technology

As of 2026-08-01 · Engagemii indexCheck another site →The index →

AI Visibility Scorecard

Refraction Networking

Refraction Networking

Unclaimed

decoyrouting.com · Technology

Borderline visible. AI bots can crawl Refraction Networking, but the structured-data signals are thin - you are at real risk of being skipped when buyers ask ChatGPT, Claude, or Perplexity for a recommendation.

AI engines read this profile 9 times

Claude · Meta AI

#859,782 of 2,705,698 in Technology for AI visibility

2

AI Naming Predictability

i

Rarely named · 2/100

More likely to be named than 81% of Technology companies

4

AEO Visibility

i

Borderline · 4.2/10

0

Muse Index Score

i

AI agent readiness

Not agent-ready · 0/100

0

AI Adoption

i

None detected · 0/100

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About Refraction Networking

from our crawl and measurement

Refraction Networking is a business whose own site puts it this way: "Ongoing work Published research Get involved Refraction Networking Internet freedom in the network’s core What is refraction networking?." To AI engines like ChatGPT and Perplexity, though, it is barely visible: it scores 4.2 out of 10.

On the page itself the strengths are clear: a clear heading structure. It is passable on a few credibility markers and partial sitemap and link coverage. What holds it back is a clearly stated business identity, the technical files AI engines look for, such as llms.txt or an open robots.txt and structured data describing the business.

Away from its own site, other sites link to it. There is some, but not much, sign that the domain is only lightly established and there is little discussion of it. Beyond that, AI engines do not yet recognise it as a distinct business, there is no press coverage to draw on and it does not come up on Reddit. Those are earned elsewhere on the web, not fixed on the site itself.

AI crawlers have visited 2 times in our tracking, including ClaudeBot (Anthropic). The site links to no social profiles, so there is nothing tying the brand to a wider presence.

Industry · Technology
Last scored · Aug 1, 2026

The 6 signals AI reads

Strong · Good · Fair · Weak

Structured Data

Weak

Organization / LocalBusiness JSON-LD that AI can read.

Content Structure

Strong

Clear headings and answer-style content.

Entity Clarity

Weak

How clearly your brand identity reads to AI.

E-E-A-T Signals

Experience, Expertise, Authority, Trust

Fair

Experience, Expertise, Authority, Trust markers.

Technical AEO

Fair

robots.txt, llms.txt, and AI-bot crawl access.

AI Discoverability

Fair

Sitemaps and entity links AI can follow.

Off-page authority

How the web signals your brand to AI

Backlinks

Good

Inbound links from other sites.

Domain Authority

Weak

Little domain authority yet.

Reference Presence

Weak

Not in AI knowledge graphs yet.

News & Press

Weak

No press coverage found yet.

Community

Weak

No community discussion yet.

Social Mentions

Weak

No social discussion found yet.

What this score means

Your AEO score measures whether AI search engines - ChatGPT, Claude, Perplexity, Gemini - can actually read your site and cite it in answers. Roughly two-thirds of sites are invisible to them. At 4.2/10, Refraction Networking is crawlable but under-signaled - fixable, and the signals above are where to start.

Frequently Asked Questions

What work is happening now?

Refraction networking was independently invented in 2011 by three engineering teams.

What research has been published?

The papers are: Operational Deployment Running Refraction Networking for Real Benjamin VanderSloot, Sergey Frolov, Jack Wampler, Sze Chuen Tan, Irv Simpson, Michalis Kallitsis, J. Alex Halderman, Nikita Borisov, and Eric Wustrow Proc. 20th Privacy Enhancing Technologies Symposium (PETS ’20), July 2020.

How can I get involved or find out more?

The refraction networking coalition is working to partner with network operators. If you’d like to find out more or help support our efforts, please contact us at [email protected]. * The term decoy routing has been used ambiguously to refer to this overall family of approaches and to a specific scheme described by Karlin et al. We use refraction networking as an umbrella term to refer to all the schemes.

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Source & Attribution

Scored by Engagemii on August 1, 2026. Methodology: engagemii.com/aeo/methodology

Source URL: https://engagemii.com/aeo/brands/decoyrouting

Cite this score: Engagemii (2026). "AEO Score for Refraction Networking." Retrieved from https://engagemii.com/aeo/brands/decoyrouting

Licensed under CC BY 4.0. You may reuse this data with attribution: a visible link to engagemii.com.

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