
Sauna reconciles stock across Shopify and your warehouse data, flags aging and overstock, drafts the markdown and transfer recommendations, and builds the weekly inventory health report.
What it does
Sauna pulls on-hand from Shopify and your warehouse export in Snowflake, reconciles the two, and writes a discrepancy list for the SKUs that don't match.
It computes days-on-hand per SKU and drafts the aging report, recommending markdown depth or a store transfer for the slow movers.
Sauna models the sell-through lift at each markdown tier from past markdowns and recommends the price that clears the unit by your target date.
It assembles the weekly inventory dashboard in Google Sheets — turns, sell-through, weeks of supply, and aging — and posts the headline to Slack.
Put Sauna to work on this.
Get started for freeIn context
Sauna shows up where you already work — the web app, Slack, email, iMessage, and Superhuman. It reads what it needs, does the task, and comes back with the draft for your approval.
Try it
The literal prompt for this job. Open it in Sauna and it picks up from there.
“Reconcile on-hand between Shopify and the warehouse export in Snowflake, list the SKUs that don't match, and flag anything over 120 days for markdown.”
Plugs into the tools you already run — and thousands more, or any MCP server.
Good to know
No. Sauna recommends the markdown depth and the units it should clear, but the price change is staged for your approval before anything updates.
It flags the mismatch and shows both source values with timestamps. It won't pick a winner — it surfaces the gap for you to reconcile.
Sauna reads only what you connect, and acts only after you approve. Your workspace and its memory are yours, not training data.
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