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Karmyug

Catalogue and shelf data that keeps up with a SKU list that changes weekly.

Shelf recognition, catalogue attributes, visual search and support data.

Retail models rot faster than any other category. Packaging changes, a new variant ships and detection quietly degrades in the stores that matter most.

We build refresh cycles into the engagement rather than treating collection as a one-off, and we deliberately over-sample the conditions where checkout models fail.

Where AI is being applied in retail & e-commerce

The applications teams actually come to us for, rather than the full theoretical list.

  • Shelf monitoring

    Out-of-stock and planogram compliance across store formats.

  • Product recognition

    SKU-level detection including occlusion and glare.

  • Catalogue attributes

    Colour, pattern, material and style extraction at catalogue scale.

  • Visual search

    User photo to catalogue item matching pairs.

  • Support chat and calls

    Order, refund and delivery dialogue for assistant training.

  • Review and sentiment

    Aspect-level sentiment on product reviews by market.

Data security and compliance

The controls your risk team will ask about, before they ask.

  • GDPR

    EU data subject rights and DPAs

  • CCPA

    California consumer privacy

  • DPDP Act 2023

    India data protection, in-region storage

Retail & e-commerce questions

Can you capture in our stores?

Yes, with field agents under your access rules, or crowdsourced capture where store permission allows.

How do you keep up with catalogue churn?

A standing refresh batch on a cadence you set, priced per image rather than renegotiated each time.

Power your retail & e-commerce AI with data you can audit.

Start with a pilot batch against your real guidelines. You accept it before anything scales.