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consumer goods & FMCG · delivered

Counterfeit detection: capture app

Structured field evidence for a counterfeit problem that previously had none.

field ops & vision consumer goods & FMCG
store-routed capture
guided 7 to 8 step photo evidence
feeds detection ML

The challenge

Counterfeit products were suspected in certain stores, with no structured way for field agents to capture product evidence usable by a detection model.

What we built

A capture app that routes field agents to suspected stores and guides them through a 7 to 8 step photo sequence of the product. Images flow into the downstream counterfeit-detection ML pipeline.

The outcome

Every suspected store produces model-ready evidence, captured the same way every time.

WANT ONE LIKE THIS?

Bring the problem. Leave with a scope, a timeline, and the number it should move.

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FAQ

Questions we get asked about this build

What did Finzarc build for this client?

Finzarc built a capture app that routes field agents to suspected stores and guides them through a 7 to 8 step photo sequence of the product. Images flow into the downstream counterfeit-detection ML pipeline.

What problem did it solve?

Counterfeits were suspected in certain stores, and no structured way existed for field agents to capture product evidence a detection model could use. Finzarc standardised the capture.

What did it deliver?

Every suspected store produces model-ready evidence, captured the same way every time.

Can Finzarc build brand-protection tooling for us?

Yes. Bring the problem, leave with a scope. Book a call at /book.

Finzarc is an India-based AI & data-engineering studio: production automations, analytics and custom apps for enterprises, first delivery in about three weeks. This is delivered work for consumer goods & FMCG: see how Finzarc ships in about three weeks, or bring the problem and leave with a scope. Working software > promises of future.