AI Visibility Scorecard
dumarch.com · Technology
At 1.11/10, Dumarch is near-invisible in AI search today. Most AI engines will not name it when asked about its category. The weakest signals are Structured Data, Entity Clarity and E-E-A-T Signals. That is fixable, and the signals below show where to start.
AI engines read this profile 1 times
Claude
7
AI Naming Predictability
iRarely named · 7/100
Technology average 28
Top 80% of Technology
See what's behind this score →1.11
-
Network Authority
iNot connected yet
0 relationships on record. Businesses in Technology average 4. Claim your page and Engagemii is your first.
See what's behind this score →5
0
from our crawl and measurement
Dumarch describes itself simply: "Home Gallery Videos Manual Contact Special ATX power supply tester PST-64 Description of the device The PST-64 tester is intended for real, precise and professional testing of ATX power." To AI engines like ChatGPT and Perplexity, though, it is barely visible: it scores 1.11 out of 10.
Our crawl found a sitemap and a readable heading structure. It is missing structured data describing the business and an llms.txt file.
AI crawlers have read this profile once in our tracking, including ClaudeBot (Anthropic).
Strong · Good · Fair · Weak
Structured Data
Weak
Organization / LocalBusiness JSON-LD that AI can read.
Content Structure
Good
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
Weak
Experience, Expertise, Authority, Trust markers.
Technical AEO
Good
robots.txt, llms.txt, and AI-bot crawl access.
AI Discoverability
Fair
Sitemaps and entity links AI can follow.
How the web signals your brand to AI
Backlinks
Weak
No inbound links found yet.
Domain Authority
Weak
Little domain authority yet.
Reference Presence
-
Not yet measured.
News & Press
Weak
No press coverage found yet.
Community
Weak
No community discussion yet.
Social Mentions
Weak
No social discussion found yet.
Your AEO score measures whether AI search engines (ChatGPT, Claude, Perplexity, Gemini) can read your site and name it in answers. At 1.11/10, Dumarch is near-invisible to AI engines today. That is fixable, and the signals above are where to start.
What is the PST-64 intended for?
The PST-64 tester serves for real, precise and professional testing of ATX power supplies. Its purpose is to detect the worsened condition of an ATX power supply sufficiently in advance, when it is necessary to replace such an unreliable unit, or repair it while the computer or server is still undergoing maintenance. Otherwise such a unit could fail during the computer’s full operation and cause substantial damages.
Why test ATX power supplies?
A quality power input source is the basic prerequisite for the reliable operation of every computer. A lowered quality of the power source can negativelly affect the correct working of an operation system, or even cause its complete disabling, as well as damage to the motherboard of the computer, along with other peripheral boards and the hard disk, which might contain data crucial to the user.
What can the PST-64 tester do?
PST-64 offers an overview of all important properties and quantities of the power supply. It allows the monitoring of voltages without loads in real time, the overseeing of voltage fluctuation (Ripple), as well as noise (Noise), the latter an indicator of damaged filtration capacitors or damage dealt to the electrical circuit of the power supply.
What does the tester consist of?
Main switch – for activating the device. Power input connector – in case of power input through the adapter. ATX output power connectors – for connecting the outputs of the measured power supply to the tester. Display screen – displays detailed information about the measured values. LED indicator – displays the basic states of the measured values of the individual outputs.
ChatGPT doesn't crawl the web like Google does. When someone asks Claude about the best project management tools, the model isn't searching your website in real-time. It's pulling from training data that stopped months or years ago.
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Scored by Engagemii on November 9, 2026. Methodology: engagemii.com/aeo/methodology
Source URL: https://engagemii.com/aeo/brands/dumarch
Cite this score: Engagemii (2026). "AEO Score for Dumarch." Retrieved from https://engagemii.com/aeo/brands/dumarch
Licensed under CC BY 4.0. You may reuse this data with attribution: a visible link to engagemii.com.
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