Live assessment: six AI engines queried when available
Agentic Commerce Readiness for richwashburn.com
AI shopping agents are already choosing companies for buyers in this market. This measures whether they can find, trust, and recommend richwashburn.com.
Generated Jun 28, 2026Category TechnologyProtocols audited UCP, ACP, AP2
F
28 / 100
Technical Readiness Grade
Weak infrastructure
Your infrastructure score. Strong technical readiness still does not guarantee AI recommends you, that is the AI Visibility number beside it.
AI VisibilityCritical
0/100
Can an agent buy from you?No
1/4 protocols
Engines measured
4/6
live, with receipts
Engines that found you
1/6
organic model visibility
Agent parse budget
208ms
against the 300ms target
Revenue exposed
$89K/mo
modeled on agentic adoption
1 AI Visibility across the six engines
When a buyer asks an AI engine to recommend a company, does it name you? We measure every engine and label estimated fallbacks.
0
Measured average
Copilot
34
Estimated from the current ACRA score model until live receipts are available.estimated
ChatGPT
19
Estimated from the current ACRA score model until live receipts are available.estimated
Gemini
0
No organic mention across the measured buyer prompts.measured
Claude
0
No organic mention across the measured buyer prompts.measured
Perplexity
0
No organic mention across the measured buyer prompts.measured
Grok
0
No organic mention across the measured buyer prompts.measured
4 of 6 engines measured live: gemini-3.5-flash-low, claude-sonnet-4-6, sonar, grok-3-fast on Jun 28, 2026
1A What each engine needs
Each engine weights different evidence. These are the specific requirements, gaps, top fix, and score rationale for this report.
ChatGPT
not measured
Not measured this run (the AI provider account hit its usage limit). This is not a zero; the priorities and gaps below still apply.
No agentic protocol layer (UCP/ACP) - ChatGPT cannot transact with or confidently surface you.
Thin structured data - ChatGPT cannot extract your products, pricing, or answers.
No verified reviews or press for ChatGPT to validate trust.
Highest-leverage fix
No agentic protocol layer (UCP/ACP) - ChatGPT cannot transact with or confidently surface you.
Gemini
0/100
Gemini did not name you in any buyer query we asked (score 0/100). Insufficient schema - Gemini relies on it more than any other engine.
What it prioritizes
Rich schema markup (Gemini is the most schema-hungry engine)
Google Business Profile and Google-native signals
E-E-A-T and social sameAs for entity disambiguation
Your gaps
Insufficient schema - Gemini relies on it more than any other engine.
No Google Business Profile / sameAs links - breaks Gemini entity disambiguation and AI Overviews.
Weak E-E-A-T - Gemini will not treat you as an authoritative source.
Highest-leverage fix
Insufficient schema - Gemini relies on it more than any other engine.
Claude
0/100
Claude did not name you in any buyer query we asked (score 0/100). Unverified brand entity - Claude cannot confirm who you are without linked, corroborated identity.
What it prioritizes
Entity clarity (Organization schema linked via sameAs)
Demonstrable E-E-A-T and real outcomes (case studies)
Clean structured data and agent infrastructure
Your gaps
Unverified brand entity - Claude cannot confirm who you are without linked, corroborated identity.
Missing structured data - Claude reads your page as unlabelled text.
No case studies or documented outcomes for Claude to weight.
Highest-leverage fix
Unverified brand entity - Claude cannot confirm who you are without linked, corroborated identity.
Perplexity
0/100
Perplexity did not name you in any buyer query we asked (score 0/100). No citable press footprint - Perplexity ranks by third-party sources it can cite.
What it prioritizes
Citable third-party sources (Perplexity is citation-first)
Press coverage and research citations
E-E-A-T and review trust
Your gaps
No citable press footprint - Perplexity ranks by third-party sources it can cite.
No research citations or authorship depth for Perplexity to trust.
No external validation for Perplexity to reference.
Highest-leverage fix
No citable press footprint - Perplexity ranks by third-party sources it can cite.
Microsoft Copilot
not measured
Not measured this run (the AI provider account hit its usage limit). This is not a zero; the priorities and gaps below still apply.
What it prioritizes
Same OpenAI backbone as ChatGPT, plus the Microsoft business graph
LinkedIn and professional authority signals
Syndicated press and structured data
Your gaps
Weak LinkedIn / professional presence - Copilot leans on the Microsoft business graph.
No agentic protocol layer - Copilot shares ChatGPT's execution requirements.
No syndicated press for Copilot to weight as third-party authority.
Highest-leverage fix
Weak LinkedIn / professional presence - Copilot leans on the Microsoft business graph.
Grok
0/100
Grok did not name you in any buyer query we asked (score 0/100). No active X / social presence - Grok is built on the live X signal; this is its #1 input.
What it prioritizes
Live X / social presence and recency (its single biggest input)
Active public conversation and earned media
Fresh, dated content
Your gaps
No active X / social presence - Grok is built on the live X signal; this is its #1 input.
No earned media or fresh public chatter for Grok to surface.
No dated, recent content - Grok heavily favours recency.
Highest-leverage fix
No active X / social presence - Grok is built on the live X signal; this is its #1 input.
2 Where the AI purchase breaks
Every protocol an agent needs to buy from you has to be discoverable before the transaction can start.
!
UCP
Discover
Agent cannot find what you sell
!
ACP
Check out
Agent cannot complete a purchase
!
AP2
Verify trust
No mandate, enterprise AI walks
Purchase blocked
1 of 4 protocols detected
3 The buyer you never see
This is the moment that is already happening in your market, today.
Buyer asks AI
best Technology near me
AI names 3 companies
the ones it can actually read
You are not one of them
the buyer calls a competitor
You never see this happen, and you never see the sale you lost
4 Too slow for an AI to read
An agent waits about 300 milliseconds before it gives up and reads a faster competitor.
300msagent budget
208msyour load
0ms800ms1600ms
5 The nine signals AI reads
The technical pillars remain the source of truth, translated here into buyer-facing language.
01
Whether AI shopping assistants can buy from you
Currently limiting your visibility: AI shopping assistants cannot buy from you cleanly today. They can browse the site, but the signals they need to transact are missing.
02
How clearly AI can understand your business
Currently limiting your visibility: 5 of the labels AI looks for are on your site; 10 important ones are missing.
03
Whether AI search engines quote your site
Needs work: Some pages are quotable by AI; most are not yet formatted for direct citation.
04
Whether AI tools use your content in their answers
Currently limiting your visibility: Missing the depth and authorship cues AI tools use to include your content in their answers.
05
Whether AI crawlers can reach your site at all
Strong: AI crawlers can reach your site cleanly.
06
Whether AI can confirm you exist across the web
Currently limiting your visibility: 2 social profile(s) detected. AI uses these to confirm you exist as a real business.
07
What outside sources say about you
Needs work: Some outside coverage. Building more reviews and press will move this signal fast.
08
How trusted you look to AI overall
Currently limiting your visibility: AI sees you as a real business but not yet as a category leader.
09
How often AI is recommending you to buyers today
Currently limiting your visibility: AI assistants recommend you in roughly 23 of every 100 buyer queries. Inconsistent across prompts.
10
How cheaply AI can read your pages
Needs work: Machine readability is mixed. Raw facts exist, but script weight or markup noise still taxes agent parsing.
6 What it is costing you
Modeled monthly revenue exposed as buyers shift to agent-driven discovery.
$89Kper month at risk
Where the modeled exposure concentrates
35%
19%
16%
No Agentic Protocol (UCP/ACP/AP2) AI shopping agents cannot discover or purchase from your site. You are invisible to the fastest-growing commerce channel.
Missing from AI Answer Engines ChatGPT, Perplexity, and Claude are answering your category queries — but recommending competitors, not you.
Poor Generative Engine Optimization LLMs are bypassing your content for competitors with stronger E-E-A-T and topical cluster architecture.
Methodology note. Scores combine protocol checks, machine-readable signals, the nine ACRA pillars, and live model receipts when available. Missing measurements degrade to labeled estimates.
Machine-readability context. Crawlability grade B, zero-click net loss 37%, hallucination risk critical.
"
By 2028, ninety percent of B2B purchases will run through AI agents. The engines that cannot see you will not ask permission, they will simply recommend someone else.
Gartner via Digital Commerce 360: agent-mediated purchases
Each signal is scored against the routine questions a buyer in your category would actually ask an AI assistant.
Buyer queries
240 routine questions an AI assistant fields for a buyer in your category, tested across 5 AI platforms.
Per-signal score
How often you surface cleanly versus how often a similar peer does on the same query.
Versus peers
The peer median is the middle competitor in your category at the time of the scan.
Full methodology available on request
Your next step
Get a 30-minute call with our team.
On the call, we walk through the 3 gaps that matter most for your business, why each one is costing you visibility, and the order to fix them. No proposal pressure, no slide deck. Just a clear next step you can act on whether or not we end up working together.
