

Add an authentication layer to every gate, warehouse, and marketplace with counterfeit detection with computer vision. Roboflow trains models on what your genuine product actually looks like, down to the details counterfeiters get wrong, and puts that examiner's eye on a phone, a warehouse camera, or an API, at the scale of every gate, every seizure, and every listing.
AI Counterfeit Product Detection:
Venues, Events, and Field Enforcement:
Brand Protection AI at Scale:
Bring intelligence to every authentication today.
What is counterfeit detection with computer vision?
Counterfeit detection with computer vision uses deep-learning models trained on imagery of genuine products, and of known fakes where they exist, to spot the visual differences that separate authentic goods from counterfeits: logo proportion and placement errors, stitching and construction differences, print quality and registration, tag and label details, holograms and security features, and packaging construction. The models run wherever authentication happens, on a phone in a gate worker's hand, on cameras at a warehouse intake, or through an API scanning marketplace listings, and return a genuine, counterfeit, or review decision with the differences localized on the image. Roboflow has been used in the field this way, including spotting counterfeit merchandise at live events, where gate and security staff photographed suspect goods and got calls in seconds. For measuring where brand marks appear in media, see logo and sponsorship detection; for verifying your own labels in production, see packaging label inspection.
How can a model tell a good fake from the real thing?
The same way your best examiner does, by knowing the genuine article in detail, except the model never gets tired and can be everywhere at once. Counterfeiters reproduce the look; they rarely reproduce the manufacturing: the stitch count per inch, the exact logo geometry and spacing, the print method and its registration, the font cut on the care label, the weight and finish of hardware, the hologram's behavior. Models trained on your genuine product line, across angles, lighting, and wear, and on seized fakes where your team has them, learn those details as visual features, and flag deviations with the region marked on the image so a person can see what the model saw.
Can this work at a live event, on a phone, in real time?
Yes, and live events are where this has already worked. A venue's counterfeit problem is concentrated in hours: sellers around the gates before and after the show, moving product that was printed days earlier. Models run on a phone or a small edge device without needing the venue's connectivity, so a security or brand protection team photographs a shirt, a hat, or a tag and gets a call in seconds, with the tell highlighted, which turns a confrontation about opinion into a documented finding. The same phone workflow serves market sweeps, store checks, and field enforcement, and every check is logged with location, time, image, and result, which is the evidence trail enforcement actions and legal follow-ups need.
Can it integrate with our brand protection and enforcement systems?
Yes. Roboflow Inference runs on phones, edge devices, and in the cloud or your VPC, and exposes a standard API and webhooks, so authentication results flow into your existing systems: brand protection and case management platforms, marketplace takedown workflows, customs and enforcement documentation, warehouse and returns systems for intake authentication, serialization and track-and-trace databases, and alerting into Slack, Microsoft Teams, and email, through REST, webhooks, and direct database writes.