All industries

Retail

Shelves and queues out front, supplier paper at the back door.

Retail’s data problem is split across the store: the floor is visual, the back door is paper. Raru Vision reads the first; Dodo reads the second.

documents we readSupplier invoices · GRNs · delivery challans · PO documents · price lists

What we solve

Shelves that report themselves

Raru Vision · scene understanding

Stock levels, empty facings, misplaced products, and planogram drift — read per fixture, per pass, all day, from the cameras you already own.

Know the store’s rhythm

Raru Vision · scene understanding

Footfall by zone, billing-queue build-up, and dwell at fixtures — counted as anonymous totals, so ops decisions run on numbers instead of walk-throughs.

Loss prevention with context

Raru Vision · scene understanding

Pilferage-risk moments — items leaving shelves outside a checkout path, unattended zones, after-hours movement — flagged for a human to review, with the clip attached.

The back door runs on paper

Dodo · document understanding

GRNs, supplier invoices, and delivery challans arrive with every truck. Dodo turns them into structured records at the receiving desk, so inventory reflects reality the same hour.

GRN ↔ invoice ↔ PO, matched

Dodo · document understanding

Three documents describe every delivery, and they rarely agree. Extract all three into one shape and the mismatches surface themselves — before payment, not after.

Bring us your version of these problems. We’ll show you the record it becomes.

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