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Red Points provides an AI-powered brand protection platform designed to detect and remove counterfeits, piracy, impersonation, and other forms of digital infringement. The platform combines automated detection, marketplace integrations, seller network intelligence, and enforcement workflows to help brands protect revenue, reputation, and consumers across marketplaces, websites, social media, paid ads, apps, and domains. Red Points supports scalable enforcement through technology-driven, fully managed protection programs operated by expert teams, enabling organizations to address infringement at platform speed while maintaining visibility through reporting and analytics. The company operates globally with more than 300 employees and offices in New York, Barcelona, Beijing, and Salt Lake City, serving over 1,300 brands worldwide.
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The three main strengths that we're seeing with Red Points are speed of locating false or questionable sites, the usability of the Red Points portal, and lastly, Red Points' ability to successully shutdown these sites once we have given them the goahead.
The automation and detection coverage stand out. RedPoints continuously monitors major marketplaces and the broader web, surfacing infringing listings and supicious domains with a speed and breadth that no internal team could replicate manually. The takedown execution is also strong - once a case is flagged and actioned, turnaround time are generally fast and the platform provides clear status tracking so we always know where each case stands. The reporting dashboards also give us meaningful data to demonstrate enforcement activity to internal stakeholders and to inform our wider IP strategy.
The user interface is intuitive and easily understood. While there is an ongoing monthly cost for the service, the ROI is undeniable when compared to traditional legal fees. By automating the detection and takedown process, we have claimed hundreds of hours of internal productivity.
We really only have one dislike and this is how you export the site lists for review. This is partly by design so that you can see all sub-urls however, this can be a bit overwhelming for non-technical users so we export the data and manipulate this into an Excel spreadsheet first.
The main friction point could be the false positives. The detection net is cast wide, which means a non-trivial volume of flagged items require manual review before actioning. For a lean legal team, this review burden adds up. There is also room to improve the customisation of enforcement workflows: more granular rule-setting per market or infringement type would reduce back-and-forth and allow for a more tailored enforcement posture.
Initial calibration: like any sophisticated AI, the platform requires a brief 'learning period' to minimize false positives (occasionally flagging our own authorized content).