AI Visibility Scorecard
agentcontextgraph.com · Nonprofits
Borderline visible. AI bots can crawl ROIzilla, 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 2 times
Claude
#332,976 of 827,739 in Nonprofits for AI visibility
4
AI Naming Predictability
iRarely named · 4/100
Nonprofits average 9
Top 37% of Nonprofits
See what's behind this score →4
-
Network Authority
iNot connected yet
0 relationships on record. Businesses in Nonprofits average 2. Claim your page and Engagemii is your first.
See what's behind this score →45
Muse Index Score
iAI agent readiness
Agent-ready · 45/100
Nonprofits average 14
See what's behind this score →?
from agentcontextgraph.com
An agent context graph is the structured working set of entities, relationships, state, and policies an AI agent operates over for a given task. Definition, comparison with RAG and agent memory, and F
Strong · Good · Fair · Weak
Structured Data
Good
Organization / LocalBusiness JSON-LD that AI can read.
Content Structure
Strong
Clear headings and answer-style content.
Entity Clarity
Fair
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
Strong
robots.txt, llms.txt, and AI-bot crawl access.
AI Discoverability
Good
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
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.
Your AEO score measures whether AI search engines (ChatGPT, Claude, Perplexity, Gemini) can read your site and name it in answers. At 4/10, ROIzilla is crawlable but under-signaled - fixable, and the signals above are where to start.
What is an agent context graph?
An agent context graph is to an AI agent what a workbench is to a technician: only the relevant parts, laid out in relation to each other, within reach. When an agent is assigned "process this refund," the task implicitly touches a small universe — the customer, the order, the payment method, the contract terms, the refund policy, the fraud flags.
Why do agents need graph-structured context?
Because agent failures are usually relationship failures. Watch agents go wrong in production and a pattern emerges: the model rarely fails at language; it fails at knowing that this order belongs to that contract, that this approver outranks that policy exception, that these two tickets describe the same incident.
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The exact fixes for ROIzilla
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When a buyer asks ChatGPT which company to use, two different things can happen. ChatGPT can name a company in its answer. Or it can link to a web page as a source. Most advice about AI visibility is about the second one. Our data says the first one is what matters.
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Scored by Engagemii on September 6, 2026. Methodology: engagemii.com/aeo/methodology
Source URL: https://engagemii.com/aeo/brands/agentcontextgraph
Cite this score: Engagemii (2026). "AEO Score for ROIzilla." Retrieved from https://engagemii.com/aeo/brands/agentcontextgraph
Licensed under CC BY 4.0. You may reuse this data with attribution: a visible link to engagemii.com.
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