CITAQ

For Enterprise

AI readiness for catalogs at scale.

One company. Thousands of SKUs. Your own storefronts. CITAQ scores every product in your catalog for how well AI can find, cite, and recommend it — so the fix list is specific, no matter how large the catalog gets.

Your catalog · 126 SKUs
Cite-readyStrongNeeds workAt riskBroken

Every square is one SKU, scored on its own. A store-level tool would collapse this entire catalog into a single grade — and hide the handful of listings actually costing you AI visibility.

The problem

A single grade can’t tell you which listings are broken.

Hand a 3,000-SKU brand one number and you learn nothing you can act on. The catalog is never uniformly good or bad — a few hundred listings carry the risk, and the only way to find them is to score every product on its own.

A store-level tool
BCatalog grade · 3,000 SKUs

One grade for the whole catalog. Nothing to fix, nowhere to start.

CITAQ12 listings flagged
  • SK-2291Barrier Repair Cream 50ml34
  • SK-0847Vitamin C Serum 30ml (EU)41
  • SK-1163Overnight Recovery Mask47
  • SK-3390Gentle Foaming Cleanser52
  • + 8 more, ranked by AI-visibility risk

The specific SKUs to fix first — with the reason each one is losing citations.

Portfolio

One workspace across every storefront you run.

Sub-brands, regional storefronts, locale variants — connect all of your own stores to a single workspace with a shared product pool and team seats. Each storefront keeps an isolated pool, so a locale catalog never bleeds into the flagship’s numbers.

One workspacepooled products · shared seats
Flagship brand
Primary catalog
Sub-brand line
Isolated pool
EU storefront
Locale variant
APAC storefront
Locale variant

10 storefronts

one workspace, custom for higher

500 pooled SKUs

allocate across stores, custom above

25 team seats

shared access, isolated pools

API & integration

Pull scores into your own systems.

Programmatic access to scores, history, and reports — piped directly into your BI, PIM, and merchandising stack. Trigger a rescore when a listing changes, flag regressions in your own dashboards, and keep AI readiness beside the rest of your catalog data instead of in a separate tab.

Available programmatically
Scoresper SKU, per module
Historyevery rescore over time
ReportsIP-sanitized exports
into your BI · PIM · merchandising stack

The full system

Every capability runs per SKU, across the whole catalog.

The same system that scores one product runs across all of them. Here is the short version — the full breakdown lives on the features page.

Citation readiness scoring

Seven modules, a 0–100 score, and a fix list — run on every SKU, not the storefront.

13-crawler AI-access grid

Which AI crawlers can actually reach each product page, checked catalog-wide.

Marketplace readiness

Whether each listing is structured for the surfaces buyers ask AI about.

Live verification

Confirm which SKUs AI platforms cite correctly, and which they contradict.

Competitive diff

See what a more-cited competitor SKU carries that yours is missing.

Reports

IP-sanitized exports per SKU or per line, ready for internal review.

Cadence

Your catalog stays fresh at volume.

A large catalog changes constantly. Enterprise runs on daily auto-rescan through a priority processing pool, so scores keep pace with your listings instead of lagging a week behind them.

Daily auto-rescan

the whole catalog stays fresh

Priority processing pool

your runs don't wait behind smaller catalogs

5,000 scans / month

published volume, custom headroom above

Published limits are the starting point. Catalogs and scan volumes above them are handled as custom headroom — that’s part of the conversation with sales, not a hard ceiling.

Procurement

What happens when you talk to us.

Enterprise doesn’t run through the self-serve checkout. Here is what we can commit to today — described plainly, not dressed up as a program we haven’t built yet.

Custom contracts & annual invoicing

Move off self-serve monthly billing to a negotiated annual agreement invoiced to your finance team.

Dedicated onboarding & a named contact

A single point of contact walks your team through connecting storefronts and prioritizing the catalog.

Support for your security review

We answer your InfoSec and procurement questionnaires directly, in plain terms, using what actually ships today.

A formal, documented onboarding program is still taking shape. We won’t claim a rigid SLA we can’t stand behind — what we offer is a real point of contact and a scoped plan for your catalog.

Data handling

Governance your reviewers can check.

For an InfoSec or procurement review, here is exactly how CITAQ handles your catalog and credentials today — the facts, without a compliance badge we haven’t earned.

Exports never expose engine internals

Every report and data export passes through an IP-protection contract that strips 18 engine internals first. Reviewers and stakeholders see findings and fixes — scores, gaps, recommendations — never the scoring mechanics beneath them.

Credentials are soft-deleted, never silently retained

When a storefront disconnects, its Shopify OAuth token is soft-deleted and nulled — left unusable. Credentials follow a soft-delete-only policy across the platform, with no hard deletion path.

That is the whole list today. There is no SOC 2, SSO, or ISO certification yet, and we won’t imply otherwise. As the data-handling program grows, this is where it will be documented — not before it’s real.

Talk to sales.

Bring your catalog size and the storefronts you run. We’ll scope a custom contract around them — annual invoicing, dedicated onboarding, and headroom above the published limits.

Custom contracts available for large teams · sales@citaq.io