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Pillar 04 · Data & Inventory

Inventory that thinks ahead.

SKU-level margins, predictive replenishment, and answers in plain English — one source of truth for profit.

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What we build

What this looks like in your store.

Predictive restock alerts

Sales velocity and supplier lead times combined — reorder before the stockout, not after.

SKU-level margin analysis

Know which products actually make money, down to the variant.

Dead-stock detection

Slow movers flagged with markdown scenarios modeled — cash freed up, not buried.

BigQuery data layer

Your store data unified in a real warehouse — the intelligence layer, not another spreadsheet.

Ask-in-plain-English agents

“What's running low?” “What should I reorder?” — answered by agents over your live data.

Demand forecasting

Seasonality and trend baked into reorder quantities automatically.

Shipped · Proof of work

Predictive inventory across every variant, every store

Multi-store e-commerce brand

A BigQuery-backed inventory layer spanning tens of thousands of variants across multiple storefronts, with agents for stock lookup, predictive restock, and demand forecasting — queried in plain English.

FAQ

Common questions.

We run everything in spreadsheets — is that a problem?

It's the normal starting point. We move the intelligence into a proper data layer (BigQuery) and keep spreadsheets for what they're good at: config and quick edits.

Can it handle multiple stores and thousands of SKUs?

Yes — our production builds span multiple storefronts and tens of thousands of variants. The architecture is built for multi-store from day one.

What does “query in plain English” mean?

You ask questions like “what's below 14 days of stock?” in chat, and an AI agent answers from your live inventory data — no SQL, no dashboard hunting.

Get started

See what this looks like on your stack.

A free 30-minute call. We map your workflows together and show you what's worth automating.

Book a Free Discovery Call