1. AgentAudit
AgentAudit
New audit
220 controlled shopping missions · real AI agents

Can AI shopping agents actually buy from you?

AgentAudit runs 220 controlled agent trials across your catalog and measures whether AI shoppers can see your products, choose them fairly, and carry a purchase through to payment.

Merchants have SEO for Google’s crawler. This is the equivalent check for the agents now choosing products on your customers’ behalf.

Takes ~2–15 min · the demo costs $0 · spend is hard-capped at $30 per audit
What it measures
6 signals
HHI · position · framing · coverage · invisibles · stability
Headline output
0–100
AgentReady Score, CI-bounded
Confidence
95%
bootstrap CIs on every number
Money path
Gated
Razorpay test-mode, capped & human-approved
The honest part

Provider failures are counted, not hidden. If an AI agent misspells your product or the model truncates, you see it in the failure rate — never a silently optimistic score.

1 · Bring your catalog
Pick the demo store, upload a CSV/JSON, or import a live Shopify-style feed. No login, no scraping of your checkout.
2 · Run 220 missions
Fixed-seed, controlled trials across 20 shopper personas and 3 test conditions. Every answer is recorded — wins and walk-aways.
3 · Read the score
One AgentReady Score with its CI, plus per-product fixes that stay human-approved until you say go.
Demo Store
RECOMMENDED
40 products · 4 categories · listing quality deliberately varied (rich, thin, minimal) so you can see what the audit catches. The fastest way to see every screen with real measured numbers.
Upload catalog
5–500 rows, JSON or CSV, ≤5 MB — per-row validation errors are shown before anything runs.
Drag & drop a .json or .csv catalog hereclick to browse · nothing runs until you approve
Connect a real store
SHOPIFYno login needed — reads the public product feed
Paste your store’s URL (e.g. mystore.myshopify.com). We import up to 100 listings as a snapshot, then run the same 220-trial audit on your real catalog.

Pick the currency your store sells in — prices arrive in the store’s own currency; non-INR is converted at a labeled fixed rate (assumption, never measured). Some stores disable the public feed; the error will say so.

Recent runs
Every audit on this backend — how far it got, what it found, and fixes to review. Runs whose engine was interrupted (server restart, provider outage) keep every recorded mission — open one to see exactly what was measured before the stop.

Loading runs…

What this tool does not do
Store imports read the public product feed — a snapshot at import time. No HTML scraping, no login, nothing touches the live storefront or its checkout. Numbers come only from real shopping missions recorded in this run — nothing is estimated in your browser. Every headline figure shows its likely range.
Proven with live data
Bounded claims, verbatim from the build state — everything below has been demonstrated end-to-end on live data, not mocked.
  • ✓Complete audit matrix executed live, end-to-end, against real imported Shopify catalogs
  • ✓Measured: walk-away rate (agents buying nothing), demand concentration, position bias with statistical significance tests, wording sensitivity
  • ✓Every headline figure shows its 95% likely range — computed from 2,000 bootstrap resamples
  • ✓Failure handling: server-restart recovery, AI-provider circuit breaker, labeled stop reasons — partial runs never render as complete
  • ✓Razorpay payment-link plumbing with verified webhooks and duplicate protection (test mode)
  • ✓One-click import from any public Shopify storefront feeds the same audit within minutes — no scraping, no login
  • ✓Live progress over server-sent events: every mission streams to the dashboard as it lands, with per-model answer rates
  • ✓AI-provider outages degrade gracefully — throttled or interrupted missions are recorded with labeled reasons and stay fully auditable
  • ✓Identical re-runs are served from the response cache at $0 marginal cost; only changed catalogs re-bill

Scope: the audit measures the association between listing quality and agent choice under the scenario assumptions you set — correlation, not causation. Store imports are point-in-time snapshots of the public product feed.

©2026 AgentAudit — every number carries its confidence interval.