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Anasayfa » Blog » Google’s Gradient invests in Patlytics to assist companies in safeguarding their intellectual property
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Google’s Gradient invests in Patlytics to assist companies in safeguarding their intellectual property

By ayaksızMayıs 1, 2024Yorum yapılmamış2 Mins Read
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Patlytics, an AI-powered patent analytics platform, aims to accelerate patent workflows for enterprises, IP professionals, and law firms, spanning discovery, analytics, comparisons, prosecution, and litigation.

Securing $4.5 million in seed funding, oversubscribed and closed within days, the fledgling startup was led by Google’s AI-focused VC arm, Gradient Ventures.

Founded by CEO Paul Lee, formerly a venture capitalist at Tribe, and CTO Arthur Jen, a serial entrepreneur who previously co-founded and served as CTO of the web3 wallet platform Magic, Patlytics was conceived from their shared vision and complementary skills. Their firsthand experiences and deep industry understanding drove the creation of Patlytics.

Lee and Jen expressed their observations of numerous opportunities in the IP space. Lee, with a background primarily in investing in vertical SaaS, AI, and several legal tech startups, encountered IP companies employing outdated methods in what he believed should be a digitized workflow. Meanwhile, Jen, during his tenure at Magic, gained extensive experience in filing and defending patents to safeguard company technology.

In an exclusive interview with TechCrunch, Lee emphasized, “The AI revolution in patent intelligence goes beyond efficiency; it’s about fundamentally transforming how patent professionals strategize and interact with the entire patent lifecycle. Recognizing the intricate blend of technical and legal expertise necessary for patent work, we’ve designed our platform to be an indispensable ally for patent professionals.”

Lee continued to highlight the complexities and time-consuming nature of traditional patent prosecution and litigation workflows, heavily reliant on manual input. The research and discovery phase, involving searching and analyzing vast amounts of patent data, often entails significant effort, including internet searches, manual investigations, and inherently inefficient procedures.

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