![]() ![]() “I faced the ‘conversion problem’ firsthand when I ran marketing at Gusto,” Rezaei told TechCrunch via email. When buyers follow on an ad online, they often land on a generic website without a targeted call to action, and soon leave not understanding why they should buy. Rather, she pegs it on static, templated websites that don’t match the personalization delivered by ads. Jaleh Rezaei, the CEO of Mutiny, believes that the problem doesn’t lie with the ads themselves. A 2018 survey of marketers by Rakuten Marketing found that companies waste an estimated 26% of their budgets on inefficient ad channels and strategies. ![]() But the picture doesn’t brighten even after broadening out to all categories of advertising. Obviously, that’s just one segment - retail. A report from ecommerce analytics platform Glew drives the point home: In 2015, 75% of retailers that spent at least $5,000 on Facebook ads ended up losing money on those ads, with the average return on investment landing around -66.7%. Our newest partner, John Curtius, Partner at Tiger Global, said it best: “Devron's technology addresses key hurdles preventing companies from more easily and more securely gaining access to data, sharing data between organizations, and making effective use of AI.Advertising, particularly online advertising, isn’t a surefire way to bolster business. We have partnered with the best investors who believe machine learning is in its infancy - and are focused on solving full-cycle data science challenges without compromising privacy.īut don’t take our word for it. We are seeing adoption by top U.S Government Agencies and Fortune 100 customers, which are using the product to enable faster access to their distributed data without needing to anonymize or create anything synthetically. We have assembled a diverse set of experienced leaders from top PhD/Masters and Postgraduate programs along with the CIA and top banks to build an enterprise-ready data science platform for distributed data. We’re excited to partner with leading investors that have a breadth of experience in enterprise software, navigating the creation of new product categories, and recruiting top talent. Enterprise-ready data science platform for distributed data But at the time we started, the industry lacked a managed, enterprise-ready platform to enable data science on multiple distributed databases, without replicating or moving data. ![]() Organizations are increasingly gathering and producing greater volumes of more sensitive information that is used to create purchasing recommendations, to underwrite loans and to identify fraud. I founded Devron with the goal of enabling enterprise organizations to do the same without compromising privacy but also accessing much more data. We envision a world where consumers can enjoy the recommendations web and mobile products provide to them, without hesitating to give their private information. Privacy technologies have become more readily available in the last decade with the increase in compute at the point of data collection. I’m excited to announce that Devron has raised an oversubscribed $12M Series A round led by Tiger Global! This capital event comes approximately 14 months after a $3M Series Seed round led by Fintech Collective, along with Afore Capital, Essence VC and a number of strategic angels. Founded in 2020, our story began when the founding team saw major challenges in realizing the value from AI due to lack of access to data across the U.S Intelligence Community, and Financial Services/FinTech Sector.
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