Get your products
chosen by AI.

Shoppers now ask ChatGPT, Gemini, Perplexity and Copilot what to buy, and AI agents are starting to check out for them. MaximusLabs makes your catalog readable, your products recommendable and your store ready for agent checkout, then measures every AI shopping answer in Max Visibility.

Product answers tracked across every major AI model

Trusted by B2B teams at

  • UnderDefense
  • HROne
  • EasyWebinar
  • Oliv AI
  • B2Brain
  • Explorium
  • EdgeLabs
  • Luca AI
  • Nidra
  • Teamvoy

In short

What agentic commerce optimization is, in two sentences.

Agentic commerce optimization makes your products the ones AI shopping assistants recommend, and the ones AI agents can actually buy.

MaximusLabs fixes the four things an agent checks, then measures every AI shopping answer that names you.

What an AI agent checks before it recommends you

The MaximusLabs four-layer model
  • Layer 1Find

    AI crawlers reach your product pages, and your feeds are live where each platform reads them.

  • Layer 2Read

    Every product has complete, matching attributes in the feed and in the page's structured data.

  • Layer 3Trust

    Reviews, ratings, returns and shipping an agent can check, plus the sources AI already cites.

  • Layer 4Buy

    A checkout an agent can complete, wherever the platform supports it today.

01 · AI shopping answers#shopping-answers

Be the product
AI shows first.

We run the shopping questions your buyers ask on every AI model and record which products appear, in what order, at what price and with what rating.

  • Product mentions

    Which of your SKUs AI names, and for which prompts.

  • Price and rating accuracy

    Whether the answer shows today's price, stock and rating.

  • Rival products

    Who takes the first slot when you don't, and why.

Sample shopping answers for Acme: the first product each AI model names for one prompt, a price mismatch on Perplexity, and Acme's share of first slots
“Best trail running shoes for wide feet under $150”
Shopping prompt · 8 models · 3 runs each · Oct 14
Sample answers for Acme: the first product each AI model names for one shopping prompt, Acme's rank and the price shown
ModelFirst product namedAcme rankPrice shown
ChatGPTAcme Ridge W#1$138
GeminiKestrel Trail GTX#2$138
Google AI ModeAcme Ridge W#1$138
PerplexityLumen Glide W#3$129
CopilotKestrel Trail GTXNot named—
ClaudeAcme Ridge W#1no price
Price mismatchPerplexity · 3 of 3 runs
Answer shows $129. Your store says $138.Source: a four-month-old cached product page. Fix: refresh the feed and add a price-valid-until date to the page markup.
First slot · 140 prompts
Acme
46%
Kestrel
31%
Lumen
17%
02 · Product feeds#product-feeds

Feeds an agent
can actually read.

AI shopping answers are built from product data. We audit and fix the feeds each platform reads, so every SKU carries complete, current attributes.

  • Feed audit

    Fill rate for every attribute, by SKU and category.

  • Merchant programs

    Google Merchant Center and the ChatGPT merchant feed, set up and kept healthy.

  • Freshness

    Price and stock updates fast enough that answers never go stale.

Sample feed audit for Acme: attribute fill rates, where the feed is sent and how often price and stock refresh
Feed audit · 1,240 SKUs
Attribute fill rate across the product feed and product pages
74%
Feed health
Sample feed audit for Acme: fill rate and status for each group of product attributes
AttributeFill rateStatus
id · gtin · brand
100%
Complete
price · availability
96%
48 stale
size · width · color
61%
Variants split
material · drop · weight
42%
In images only
shipping
82%
US only
return policy
0%
Missing
Where the feed goes3 destinations
Google Merchant CenterLive · 3 warnings
ChatGPT merchant feedApplied
Microsoft Merchant CenterNot connected
Freshness · price and stock
Weekly
Now
Daily + API
Target
Full daily snapshot, with price and stock pushed by API in between.
03 · Product schema#product-schema

Pages that match
your feed.

Google checks your product pages against your feed. We add schema.org Product markup with offers, ratings, returns and shipping, and make sure both sources agree.

  • Product and offer markup

    Price, availability, GTIN and variants in JSON-LD.

  • Returns and shipping

    Return windows and delivery times machines can read.

  • Feed-to-page match

    Every mismatch between page and feed, flagged before AI sees it.

Sample Product JSON-LD for an Acme shoe page, and a feed-to-page check that flags one stock mismatch
acme.co/products/ridge-w · JSON-LDValid · Rich Results Test
{
  "@context": "https://schema.org",
  "@type": "Product",
  "name": "Acme Ridge W",
  "gtin13": "0812345678901",
  "brand": { "@type": "Brand", "name": "Acme" },
  "aggregateRating": {
    "@type": "AggregateRating",
    "ratingValue": 4.7, "reviewCount": 2184 },
  "offers": {
    "@type": "Offer",
    "price": 138.00, "priceCurrency": "USD",
    "availability": "https://schema.org/InStock",
    "shippingDetails": { "@type": "OfferShippingDetails" },
    "hasMerchantReturnPolicy": {
      "@type": "MerchantReturnPolicy",
      "merchantReturnDays": 60 }
  }
}
Sample feed-to-page check for one Acme SKU
FieldFeedPageMatch
price138.00138.00✓
stock · size 12in_stockBackOrder✕ fix
return_days6060✓
04 · Agent readiness#agent-readiness

Know your
readiness level.

We score your store on all four layers, Find, Read, Trust and Buy, then fix the gaps in order of impact. It starts with letting the right AI crawlers in.

  • Readiness levels

    A score per layer and the single biggest gap in each.

  • Crawler access

    Which AI crawlers your robots.txt and CDN let in or block.

  • Readable without JavaScript

    Price, stock and reviews in the HTML that crawlers fetch.

Sample readiness audit for Acme: scores for Find, Read, Trust and Buy, AI crawler access, and what a crawler sees without JavaScript
Agent readiness · Acme
MaximusLabs readiness audit · Oct 2026
Level 2 of 4
Find92
PerplexityBot is blocked at the CDN.
Read64
Material and drop exist only in product images.
Trust71
Return policy is missing from the feed.
Buy20
No agent checkout path on any platform yet.
Crawler access · robots.txt + CDN5 of 40+
OAI-SearchBotAllowed
GooglebotAllowed
BingbotAllowed
PerplexityBotBlocked by CDN
GPTBotBlocked · training only, your call
Page fetched without JavaScript
Price and stockIn HTML
Size chartIn HTML
ReviewsLoaded by JS
05 · Agent checkout#agent-checkout

Ready when the
agent says buy.

Agent checkout runs on new open protocols. We set up the merchant programs each platform needs and track every spec change for you.

  • Protocol readiness

    ACP, UCP and the payment rails behind them, mapped to your stack.

  • Merchant applications

    The programs that let AI platforms sell your products.

  • Spec watch

    Each change checked against the owner's official docs.

Agent checkout protocols as of October 2026 (ACP, UCP, AP2, MCP), a sample Buy-layer checklist for Acme and the monthly spec watch
Agent checkout: the protocols that exist today
Agent checkout protocols as of October 2026, checked against each owner's official docs: what each does and what MaximusLabs sets up
ProtocolWhat it doesWhat we set up
ACPOpenAI and StripeOpen standard for product feeds and agent checkout in ChatGPT. Merchants can now keep their own checkout.Merchant application, ACP product feed, checkout path
UCPGoogle and retail partnersCheckout on eligible listings in AI Mode and the Gemini app. US pilot, rolling out.Merchant Center opt-in (native_commerce), feed fixes
AP2Google and payments partnersProves the shopper authorised what the agent pays for.Compatibility check with your payment provider
MCPStarted at Anthropic, now openConnects AI assistants to tools and data, like your catalog.Catalog tools where your platform offers them
Buy layer · Acme2 of 4 done
✓Return and shipping policy URLs in the feed
✓ChatGPT merchant application submitted
◐Payment provider support confirmed
○Test order placed through an agent
Spec watchChatGPT, Google, Copilot and Perplexity checkouts all changed in 2026. We re-check each against its official docs monthly.OpenAI · Google · Microsoft · Perplexity
06 · Reviews and trust#reviews-and-trust

Give AI a reason
to trust you.

AI shopping answers lean on reviews, return terms and the sites they already trust. We strengthen the signals that make an agent confident naming you.

  • Review signals

    Volume, recency and the themes AI repeats from your reviews.

  • Merchant policies

    Returns, shipping and warranty, stated plainly and the same everywhere.

  • Third-party sources

    The review sites, forums and roundups AI cites for your category.

Sample review themes AI repeats about an Acme shoe, the source types AI cites for trail shoes, and a strategist note
What AI repeats about Acme Ridge W
Review themes found in 412 AI answers · last 30 days
Rating4.7 ★
Reviews2,184
Newest2 days
Returns60 days
Fits wide feet without sizing upin 64% of answers
Easy 60-day returnsin 31% of answers
Grip on wet rock is "average"in 18% of answers
Runs half a size small (old model)in 22% of answers
Sources AI cites · trail shoesby type
Review sites
34%
Forums
27%
Editorial lists
21%
Brand sites
12%
Strategist note"Runs small" comes from reviews of the 2024 model. Split old reviews from the new SKU and update the size guide.
07 · Comparison prompts#comparison-prompts

Win the
shortlist.

Buyers ask AI to compare, shortlist and pick. We map those prompts for your category and build the pages and proof that win them.

  • Prompt map

    Best-for, versus, alternatives and budget prompts in your category.

  • Comparison content

    Honest comparison and buying-guide pages AI can quote.

  • Gap briefs

    Every prompt you lose becomes a brief with a clear fix.

Sample comparison-prompt matrix for Acme across six AI models, with the gap brief for one lost prompt and the prompt-type mix
Acme's rank on comparison prompts
Position in the answer, by model · — means not named
36 of 140 shown
Sample comparison-prompt matrix for Acme: its position in each AI model's answer, or not named
PromptChatGPTGeminiGoogle AI ModePerplexityCopilotClaude
Best trail shoe for wide feet1213—1
Acme Ridge W vs Kestrel Trail GTX112121
Kestrel Trail GTX alternatives3——2—4
Trail shoes with free returns under $150211—32
Most durable trail shoe for rocky ground——4——3
Gap"Kestrel Trail GTX alternatives"
Acme is missing on 3 of 6 models. The answers cite two buying guides that don't list you.
→ Brief: "Wide-fit trail shoes compared" guide→ Outreach: pitch both cited buying guides
Prompt map · 140 prompts
Best-for 38%Versus 24%Alternatives 22%Budget 16%
08 · Measured in Max Visibility#measurement

See what AI
shopping earns.

Every engagement runs on Max Visibility, our platform for every AI model: product visibility, the AI bots reading your store and the orders AI sends.

  • Product visibility

    Products, prices and ratings inside AI shopping answers.

  • Agent analytics

    AI crawler logs, crawlability and agent readiness.

  • AI referrals

    Sessions and orders from AI assistants, via GA4.

Sample Max Visibility shopping trend for Acme since the engagement started, with AI bot visits and AI-referred sessions
Max Visibility/Shopping · since engagement startLast 90 days ▾
Product visibility41%↑ 17 pts
AI-referred orders312↑ 2.1×
AI bot visits48.6k↑ 34%
AcmeCategory average┊ Feed fix shipped┊ Comparison guide live
Agent analytics · product pagesserver logs
ChatGPT-User14.2k
OAI-SearchBot11.8k
PerplexityBot6.1k · unblocked
Claude-User3.4k
AI referrals · GA4
9,840
Sessions
3.2%
Order rate
ChatGPT · Gemini · Claude · other
09 · How we work#how-we-work

Five steps,
then repeat.

A brand strategist leads every engagement. We start by reading your store the way an agent does, fix what blocks a recommendation, then measure the result in Max Visibility.

  1. 01 · Audit

    Read it like an agent

    Crawl, feeds, schema and live AI shopping answers, scored on four layers.

    Readiness auditLevel 2 of 4 · 12 gaps
  2. 02 · Map

    Map the questions

    The shopping prompts in your category, by model and buying stage.

    Prompt map140 prompts · 4 types
  3. 03 · Fix

    Fix the data

    Feed attributes, product schema, policies and crawler access, in impact order.

    Feed and schema fixes6 attributes · 1,240 SKUs
  4. 04 · Earn

    Earn the shortlist

    Comparison guides, review signals and the sources AI already cites.

    Briefs and outreach4 briefs · 2 sources pitched
  5. 05 · Measure

    Measure and repeat

    Product visibility, agent visits and AI-referred orders, monthly.

    Max VisibilityMonthly shopping report
10 · Why MaximusLabs#why-maximuslabs

Why MaximusLabs

Feed tools fix data. SEO agencies fix pages. We make AI choose your products, and prove it in Max Visibility.

From the founder

AI search is a positioning problem before it's a technical one.

That's why every engagement starts by reading what AI already believes about you. You can't change a story you haven't read.

Krishna Kaanth M, Founder, MaximusLabs
Table 1. How MaximusLabs agentic commerce compares with a traditional SEO agency and a product feed tool.
What you getSEO agencyFeed toolMaximusLabs
Starts from how AI describes your brand
Tracks your products inside AI shopping answers
Fixes product feeds SKU by SKU
Builds comparison content and earns citationsPartly
Keeps you current on agent checkout protocolsPartly

30 minutes. We'll show you how AI shopping answers treat your products today.

Book a GEO strategy call
FAQ

Questions,
answered.

What ecommerce teams ask us before they start.

What is agentic commerce optimization?
Agentic commerce optimization makes your products the ones AI shopping assistants recommend and AI agents can buy. MaximusLabs fixes what agents check, from product feeds and schema to reviews and checkout readiness, then measures every AI shopping answer in Max Visibility.
How is it different from SEO or GEO?
SEO ranks pages and GEO gets your brand cited in answers. Agentic commerce works at the product level: feeds, product data, merchant signals and checkout. MaximusLabs runs all three from one strategy, because AI uses all three when it picks a product.
Which AI platforms do you cover?
Every major AI model that answers shopping questions, including ChatGPT, Gemini, Google AI Mode and AI Overviews, Perplexity, Copilot, Claude, Grok and Meta AI. MaximusLabs tracks them all in Max Visibility.
Can AI agents buy my products today?
On some platforms, for some merchants. ChatGPT, Google (UCP, a US pilot), Copilot Checkout and Perplexity Instant Buy each have their own programs and eligibility rules. MaximusLabs checks which ones fit your store and gets you ready for them.
Do I need ACP or UCP?
Most stores don't build either from scratch. Your commerce platform or payment provider often handles the protocol, while you handle the feed, the merchant program and the data quality. MaximusLabs maps what your stack already supports.
Does it work on Shopify or a custom store?
Yes. The work is feeds, structured data, policies and content, which apply to any store. MaximusLabs adapts the implementation to your platform.
How do you measure results?
In Max Visibility: product visibility in AI shopping answers, price and rating accuracy, AI bot visits to your product pages, and AI-referred sessions and orders through GA4. MaximusLabs reports them against your starting point every month.
Do you replace my feed management tool?
No. Feed tools move the data; MaximusLabs decides what the data should say, fixes the gaps and measures whether AI recommends you.
How soon do products show up in AI answers?
It depends on your category, your starting point and how fast fixes ship. MaximusLabs sets the baseline first and shows movement model by model as each change lands, rather than promising a date.

Be the product
AI puts in the cart.

Book a call. We'll run a few of your category's shopping prompts live and show you where your products stand.

This page is coming soon.