For brand owners

Stop counterfeits and brand abuse online

HAKKIU finds counterfeit listings, unauthorized sellers and lookalike domains across your channels — and prepares the takedowns to remove them. Never charged per detection or per takedown.

The problem, in plain terms

Your product turns up on AliExpress. Someone else is selling it on Amazon. A lookalike domain is running ads against your name and phishing your customers. Usually you find out by accident — a customer complaint, or a Google Alert. Checking every marketplace by hand does not scale, and each counterfeit chips away at margin and trust. HAKKIU makes finding them a background job instead of a fire drill.

How it works

Detect
Continuous AI monitoring across marketplaces, social commerce, app stores, domain registries and the open web finds listings, sellers and domains that misuse your brand.
Review
A tiered pipeline scores every match by risk and captures evidence; a person reviews consequential decisions before anything is sent — so you act on real infringements, not noise.
Remove
A trademark or DMCA notice is prepared with the evidence attached and routed to the right marketplace portal, abuse contact or domain complaint, and each case is tracked to resolution.

What that looks like on each channel

"Everywhere online" is easy to say. In practice the abuse looks different depending on where it lives, and so does the way you get it removed.

Marketplaces

Counterfeit listings and unauthorized sellers on Amazon, eBay, Etsy, AliExpress and Alibaba. Where a marketplace runs its own brand-protection route — Amazon Brand Registry, eBay's VeRO programme — notices are routed through it, which is usually the fastest way to a removal.

Domains

Lookalike and typosquatted domains running ads against your name or phishing your customers. The WHOIS record is captured with the rest of the evidence, and where it is warranted a UDRP complaint is prepared to go after the domain itself, not just one page.

Social & app stores

Fake shops, impersonation accounts and knock-off apps across Instagram, Facebook, TikTok and the app stores. These get reported through each platform's own channel, with the evidence attached so the report is not just a flag.

Coverage and pricing

See every channel HAKKIU watches in the coverage overview. Pricing is tailored to your brand and shared after a demo — you are never charged per detection or per takedown, so growing your monitoring never means a growing bill. If you're a law firm protecting client brands, see HAKKIU for law firms.

See it on your own brand
Book a demo and we'll show you what HAKKIU detects across your marketplaces, social channels and domains. Questions first? Email info@hakkiu.com.

Questions brand owners ask us

Which marketplaces and channels does HAKKIU monitor?

Marketplaces like Amazon, eBay, Etsy, AliExpress and Alibaba, plus Shopify storefronts, social commerce on Instagram, Facebook and TikTok, app stores, Google Shopping, and domain registries and the open web. The idea is to cover the places a counterfeit or a lookalike domain actually shows up, not just the one or two you already watch by hand.

How is pricing structured?

It is a flat rate, set by how many brands and marks you are protecting — not by how many infringements we find or how many takedowns we file. That matters, because the months you most need enforcement are the months a per-takedown tool costs you the most. We share the number after a demo, once we know what you are protecting.

What happens after a counterfeit listing is detected?

The match is scored by risk and its evidence is captured automatically — screenshots, WHOIS and a hashed, timestamped record. You review it, and if it is a real infringement a trademark or DMCA notice is prepared with that evidence attached and routed to the right marketplace portal, abuse contact or domain complaint. Each case is then tracked until it is resolved.

How much is automated, and where does a person actually look?

Detection is the automated part: a tiered pipeline runs keyword and typosquat checks, perceptual image hashing, then a vision-language model to judge the harder cases. But a person reviews the consequential decisions before any notice goes out. You are not handing enforcement to a model and hoping — the automation does the searching, a human makes the calls that carry weight.