Shared ACRA report for www.adamsilvaconsulting.com · generated June 30, 2026 · Get your own ACRA report

Website screenshot for www.adamsilvaconsulting.com

A94

www.adamsilvaconsulting.com captured Jun 30, 2026

The agentic-commerce readiness standard, measured live across six AI engines

Agentic Commerce Readiness for www.adamsilvaconsulting.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 Adam Silva Consulting.

Generated Jun 30, 2026Category agentic commerce consultingProtocols audited UCP, ACP, AP2

ACRA verdict

AI agents can find, trust, and buy from this business.

This is the hard grade for whether an AI agent can find Adam Silva Consulting, trust it, and complete a purchase.

Verified AI company

/ 100

AI VisibilityCritical

0/100

2 of 6 engines surfaced the business organically.

Can an agent buy from you?Yes

4/4 protocols

Engines measured

4/6

live, with receipts

Engines that found you

2/6

organic model visibility

Agent parse budget

321ms

against the 300ms target

Revenue exposed

$0/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

100

gpt-5.5

Asked heuristic fallback

Estimated from the current ACRA score model until live receipts are available.

Estimated: Jun 30, 2026

Gemini

gemini-3.5-flash-low

Asked best agentic commerce consulting companies

No organic mention across the measured buyer prompts.

Not surfaced organically

Claude

claude-sonnet-4-6

Asked best agentic commerce consulting companies

No organic mention across the measured buyer prompts.

Not surfaced organically

Perplexity

sonar

Asked best agentic commerce consulting companies

No organic mention across the measured buyer prompts.

Not surfaced organically

Copilot

gpt-5.5

Asked heuristic fallback

Estimated from the current ACRA score model until live receipts are available.

Estimated: Jun 30, 2026

Grok

grok-3-fast

Asked best agentic commerce consulting 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.

Measured average

ChatGPT

100

Estimated from the current ACRA score model until live receipts are available.estimated

Copilot

Estimated from the current ACRA score model until live receipts are available.estimated

Gemini

No organic mention across the measured buyer prompts.measured

Claude

No organic mention across the measured buyer prompts.measured

Perplexity

No organic mention across the measured buyer prompts.measured

Grok

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 30, 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

Lowest remaining engine score

Not measured this run (the request timed out). This is not a zero; the priorities and gaps below still apply.

What it prioritizes

ACP checkout + UCP product manifest (the Instant Checkout execution surface)
Verified reviews and FAQ-style structured data
A discoverable agent manifest for tool use

Microsoft Copilot

not measured

Not measured this run (the request timed out). 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

Gemini

0/100

Gemini did not name you in any buyer query we asked (score 0/100). Build the signals this engine relies on.

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

Claude

0/100

Claude did not name you in any buyer query we asked (score 0/100). Build the signals this engine relies on.

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

Perplexity

0/100

Perplexity did not name you in any buyer query we asked (score 0/100). Build the signals this engine relies on.

What it prioritizes

Citable third-party sources (Perplexity is citation-first)
Press coverage and research citations
E-E-A-T and review trust

Grok

0/100

Grok did not name you in any buyer query we asked (score 0/100). Build the signals this engine relies on.

What it prioritizes

Live X / social presence and recency (its single biggest input)
Active public conversation and earned media
Fresh, dated content

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

Protocol detected for agents

ACP

Check out

Protocol detected for agents

AP2

Verify trust

Protocol detected for agents

Purchase enabled

4 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 agentic commerce consulting 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

321msyour load

0ms800ms1600ms

5 The nine signals AI reads

The technical pillars remain the source of truth, translated here into buyer-facing language.

Worst failing signal

How cheaply AI can read your pages

Strong: Strong machine-readable HTML. Agents can reach substantive facts without excessive script or markup overhead.

How often AI is recommending you to buyers today

Strong: AI assistants recommend you in roughly 83 of every 100 buyer queries. Strong signal.

What outside sources say about you

Strong: Outside sources cover you above average for your category.

Whether AI can confirm you exist across the web

Strong: 32 social profile(s) detected. AI uses these to confirm you exist as a real business.

How trusted you look to AI overall

Strong: AI treats you as a trusted business in your category.

Whether AI search engines quote your site

Strong: AI search engines can quote you cleanly.

Whether AI shopping assistants can buy from you

Strong: Strong setup.

How clearly AI can understand your business

Strong: 44 of the labels AI looks for are on your site; 1 important ones are missing.

Whether AI tools use your content in their answers

Strong: AI tools include you in their answers.

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

9 data points pulled from independent sources, not your own site

Authority and identity

Verified entityai tool

Wikidata entityQ138829358

Wikipedianone

Schema.org types0

Press and media

Self-published pages10

Earned media mentions46

Independent pressyes

Social profiles0

Business footprint

Case studies0

Source links

Wikidata Owned media Owned media Adam Silva Consulting - LinkedIn President at Adam Silva Consulting, Inc. - LinkedIn Adam Silva Consulting: Agentic AI | Fort Lauderdale FL - Facebook

5B Third-party reviews AI can verify

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 www.adamsilvaconsulting.com stands and the exact gap to close.

3platforms to work on

G2ok

5 4.7 rating

clears the 5+ bar

AI checkout eligibility

Review source

Trustpilotlow

3 4.0 rating

7 short of the 10 bar

TrustScore visibility

Review source

Google Businessok

7 5.0 rating

clears the 5+ bar

star rating in AI search answers

Review source

Capterranone

n/a

no profile yet, need 3+

category listing

Clutch?

n/a

profile found, count not readable

verified badge

Review source

BBBok

A+

Grade A+

accreditation and grade

Review source

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.

$0per month at risk

Where the modeled exposure concentrates

Lost discovery AI never surfaces you

Lost trust ranked below rivals

Zero-click answered without a visit

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.

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 low.

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

See where you are losing buyers.

See my score10 signals

Score94 / 100

Grade letterA

TierStrong

Scan runJun 30, 2026 · v3.2

Signal 01 of 10

How this is measured

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

Keep the report current while AI buying changes.

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.

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