Nothing ison fire yet.That's the job.
The SKU that runs out in nine days. The PO two weeks late. The return rate that tripled on one variant. Mnemos keeps the record and runs the same twelve checks every week — so the quiet problems get caught while they're still quiet.
It reads the whole operation before it says anything.
No modelling exercise, no data team. Install it read-only and it walks the catalogue, the locations, the open POs and the last ninety days of orders — then tells you what it found.
| 01 | Catalogue · SKUs and variants | 4,218 |
| 02 | Channels + locations | 6 · 3 |
| 03 | Orders on record, trailing 90 d | 12,640 |
| 04 | Open purchase orders | 14 |
| 05 | Time to first answer | 14 min |
| 06 | Weekly checks, deterministic | 11 + 1 |
One grant from the Shopify App Store. No engineering, no warehouse, no data team — and no write scopes to revoke later.
Catalogue, channels, locations, inventory, orders, fulfillments, POs, returns — read end to end, then reported back as a count.
Plain language in, an answer out, with the rows it read attached. If the data will not support an answer, it says so.
The same twelve checks against current data every week, with what changed since the last run.
Answer. Watch. Remember. Review.
Mnemos is not a dashboard you have to interpret. It is an employee who has read the record and will show you the rows it read.
Twelve checks. The same twelve, every week.
Eleven are deterministic rules over your own data — same inputs, same output, every time. The twelfth is whatever the agent noticed that the other eleven would have missed. Nothing new is shipped on a whim; every check has a name and a row.
SKUs whose cover runs out before the purchase order that would refill them arrives.
stockout_before_restockWhat you're low on this week, given lead time, current velocity, and what's already inbound.
reorder_nowPOs past their expected date, ranked by the demand each one is holding up.
late_purchase_ordersDemand you couldn't fill last week because something was out of stock, priced at your own margin.
lost_sales_to_stockoutsProducts bought together often enough, and at enough margin, to be worth selling together.
bundle_candidatesVariants returning well above their own baseline, with when the shift started.
return_rate_outliersInventory that has not moved in weeks, and what holding it is costing you.
slow_moversLive products with no sales and no changes — the quiet tail of the catalogue.
stale_listingsCodes and price points moving volume below the margin you set.
margin_eating_discountsProducts accelerating or falling away against their own trend, not against an average.
velocity_shiftsWhere demand moved between channels and locations, and what moved with it.
channel_mix_shiftsWhat the agent noticed this week that none of the eleven checks are built to see.
agent_insightShopify first, then everywhere else the truth lives.
The census starts with your store. Every other connector adds a column to the same picture — never a second picture to reconcile.
Install from the App Store and the census begins immediately — no keys to paste, no pipeline to build. Mnemos requests read scopes only: it can see your operation and it cannot change it.
Or ask from Claude. Or Cursor.
Every workspace gets its own MCP server. Point your editor or assistant at it and your operation is just there, in the tool you already had open.
- 01One server per workspace, scoped to that workspace's data
- 02The same read-only access the web app has — nothing more
- 03Answers arrive with their evidence there too
{
"mcpServers": {
"mnemos": {
"url": "https://api.mnemos.ai/mcp/acme-supply",
"headers": {
"Authorization": "Bearer mn_live_…"
}
}
}
}A base plan and a credit meter.
1 credit ≈ 1 answer. Seats and connectors are unlimited on every tier, and the first 14 days are free — charging per seat would only teach your team not to ask.
| No. | Tier | Credits / mo | Price |
|---|---|---|---|
| 01 | FreeRun the census, read the first weekly review. | 0 | $0 |
| 02 | StarterOne store, one operator, questions all week. | 1,000 | $499 |
| 03 | GrowthMost pick thisA team asking through the week, across systems. | 3,000 | $699 |
| 04 | ScaleSeveral stores, several channels, heavy use. | 10,000 | $999 |