The agentic-commerce readiness standard, measured live across six AI engines
Agentic Commerce Readiness for omniconflux.com
AI shopping agents are already choosing companies for buyers in this market. Not by ranking pages, by whether they can find you, trust you, and complete a purchase. This grades exactly that for omniconflux.com.
Generated Oct 4, 2026Category autonomous AI software engineering platformProtocols audited UCP, ACP, AP2
ACRA verdict
D
Not ready for AI-led buying.
This is the hard grade for whether an AI agent can find omniconflux.com, trust it, and complete a purchase.
53
/ 100
AI VisibilityCritical
12/100
3 of 6 engines surfaced the business organically.
Can an agent buy from you?No
1/4 protocols
Engines measured
4/6
live, with receipts
Engines that found you
3/6
organic model visibility
Agent parse budget
101ms
against the 300ms target
Revenue exposed
$49K/mo
modeled on agentic adoption
0A Receipts from the live measurement
Every engine row shows the prompt, model version, date, and evidence used for the score.
ChatGPT
0
gpt-5.6-sol
Asked best autonomous AI software engineering platform companies
No organic mention across the measured buyer prompts.
Not surfaced organically
Gemini
0
gemini-3.6-flash-high
Asked best autonomous AI software engineering platform companies
No organic mention across the measured buyer prompts.
Not surfaced organically
Claude
50
claude-sonnet-5
Asked heuristic fallback
Estimated from the current ACRA score model until live receipts are available.
Estimated: Oct 4, 2026
Perplexity
50
sonar
Asked heuristic fallback
Estimated from the current ACRA score model until live receipts are available.
Estimated: Oct 4, 2026
Copilot
47
gpt-5.6-sol
Asked best autonomous AI software engineering platform companies
aged SaaS operating model.…
Found via model response
Grok
0
grok-4.5
Asked best autonomous AI software engineering platform companies
No organic mention across the measured buyer prompts.
Not surfaced organically
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.
12
Measured average
Claude
50
Estimated from the current ACRA score model until live receipts are available.estimated
Perplexity
50
Estimated from the current ACRA score model until live receipts are available.estimated
Copilot
47
aged SaaS operating model.…measured
ChatGPT
0
No organic mention across the measured buyer prompts.measured
Gemini
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: gpt-5.6-sol, gemini-3.6-flash-high, grok-4.5 on Oct 4, 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.
Claude
not measured
Lowest remaining engine score
Not measured this run (a temporary measurement error). This is not a zero; the priorities and gaps below still apply.
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
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
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 external validation for Perplexity to reference.
Highest-leverage fix
No citable press footprint - Perplexity ranks by third-party sources it can cite.
ChatGPT
0/100
ChatGPT did not name you in any buyer query we asked (score 0/100). No agentic protocol layer (UCP/ACP) - ChatGPT cannot transact with or confidently surface you.
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.
Highest-leverage fix
Insufficient schema - Gemini relies on it more than any other engine.
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.
Highest-leverage fix
No active X / social presence - Grok is built on the live X signal; this is its #1 input.
Microsoft Copilot
47/100
Microsoft Copilot actively recommends you in buyer queries (score 47/100). Hold the lead by closing the gaps below.
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.
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 autonomous AI software engineering platform 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
101msyour load
0ms800ms1600ms
5 The nine signals AI reads
The technical pillars remain the source of truth, translated here into buyer-facing language.
01
Worst failing signal
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.
06
Whether AI can confirm you exist across the web
Currently limiting your visibility: 1 social profile(s) detected. AI uses these to confirm you exist as a real business.
07
What outside sources say about you
Currently limiting your visibility: Outside sources rarely mention you. AI cannot find independent proof you exist or matter.
09
How often AI is recommending you to buyers today
Mixed: AI assistants recommend you in roughly 48 of every 100 buyer queries. Inconsistent across prompts.
08
How trusted you look to AI overall
Mixed: AI sees you as a real business but not yet as a category leader.
02
How clearly AI can understand your business
Solid: 9 of the labels AI looks for are on your site; 9 important ones are missing.
04
Whether AI tools use your content in their answers
Solid: AI tools include you in their answers.
10
How cheaply AI can read your pages
Strong: Strong machine-readable HTML. Agents can reach substantive facts without excessive script or markup overhead.
03
Whether AI search engines quote your site
Strong: AI search engines can quote you cleanly.
05
Whether AI crawlers can reach your site at all
Strong: AI crawlers can reach your site cleanly.
5A What AI found out about you
Independent data points the scan pulled from sources beyond your own site. These are the facts AI engines cross-check before they trust you.
What AI found out about you
7 data points pulled from independent sources, not your own site
Reviews are the trust layer AI engines check before recommending you. These are your live counts and the gap to each platform's bar.
Third-party reviews AI can verify
AI shopping engines trust businesses real customers have reviewed. Some commerce surfaces require review depth before they trust a merchant. Here is where omniconflux.com stands and the exact gap to close.
7platforms to work on
G2none
n/a
no profile yet, need 5+
AI checkout eligibility
Trustpilotnone
n/a
no profile yet, need 10+
TrustScore visibility
Google Businessnone
n/a
no profile yet, need 5+
star rating in AI search answers
Capterranone
n/a
no profile yet, need 3+
category listing
Clutchnone
n/a
no profile yet, need 3+
verified badge
BBBnone
n/a
no BBB accreditation yet
accreditation and grade
Yelpnone
n/a
no profile yet, need 5+
star rating display
6 What it is costing you
Modeled monthly revenue exposed as buyers shift to agent-driven discovery.
$49Kper month at risk
Where the modeled exposure concentrates
64%
22%
15%
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.
No Press / PR Coverage Press releases are the #1 fast-track to AI authority. Without them, your brand authority score stagnates as competitors get cited.
Weak Social Authority Social proof is an LLM trust signal. Low social authority reduces AI recommendation frequency by up to 40%.
The plan
Your prioritized path to recommended
Every gap above, ordered by what to fix first. Close these and AI engines move you from invisible to the company they name.
1
Fix first
Critical gaps blocking AI from transacting with or trusting you
No UCP Profile
Your site has no UCP profile at /.well-known/ucp (the official Google path) or the legacy /.well-known/ucp/manifest.json. AI shopping agents cannot discover your product catalog.
AI agents cannot read your pricing, availability, or product specifications. Your catalog is invisible to agentic commerce flows.
No Review Site Profiles Found
No profiles detected on G2, Trustpilot, Capterra, Clutch, BBB, or Google Business. Review platforms are primary trust signals for LLMs deciding whether to recommend your brand. Without them, AI agents have no third-party validation of your business and will route recommendations to competitors who do.
No profiles on G2, Trustpilot, Capterra, Clutch, BBB, or Google Business. These are the primary third-party trust signals LLMs use to validate brands. Without review profiles, AI agents cannot confirm your business is real, legitimate, and recommended by actual customers.
ChatGPT Instant Checkout, Claude Commerce, and Perplexity Shop require ACP-compatible endpoints. Without this, AI agents literally cannot buy from you.
No /agent.json or /ai-plugin.json means LLMs cannot load your capability schema for function calling or tool use.
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 A, zero-click net loss 10%, hallucination risk high.
"
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
Full-site deep dive
Every page, audited the way an AI agent reads it
We followed your sitemaps and root manifests to find every page your site publishes, then audited each one and wrote the specific fix for it. This is the part a one-page scan cannot see.
42
pages audited
of 42 discovered
99
average page score
100%
pages with structured data
3/11
root manifests present
Authority signals across your content (not just the homepage)
Measured across 1 content page, so a bare homepage no longer hides the work your articles already do.
Named author100%
Publication date100%
Article markup100%
Publisher markup100%
Root manifest health
The agent-protocol and crawler-guidance files checked at your web root, the way an AI agent would.
ACRA measures whether agents can find you, trust you, and complete a purchase. Review the gaps with our team, then keep rescanning as fixes ship and competitors move.
1,499 dollars per year for the premium annual subscription.
299 dollars per 10 scans for the 10 looks pack.
Monthly service plans are preferred after the assessment. Your ACRA fee is credited toward ASC services when you proceed. Affiliate discount codes are available.
