On Growth of 600%, WekaIO Appoints Ken Grohe as President and Chief Revenue Officer
WekaIO™ (Weka), the innovation leader in high-performance, scalable file storage for data-intensive applications, announced the appointment of Ken Grohe as President and Chief Revenue Officer (CRO). Ken will lead the company’s global go-to-market organization and report to CEO and Co-Founder Liran Zvibel.
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“We are delighted to see the Weka leadership team grow with strategic appointments such as Ken’s”
Grohe comes to Weka from Samsung’s Stellus Technologies, a leading data systems company that addresses the way companies capture, store, access, and process the unstructured data, where he served as CRO and drove the company’s overall go-to-market strategy. A highly seasoned veteran of the industry, Grohe previously served as President of SignNow, SVP and GM of Barracuda Networks, and CRO of Virident, a Western Digital Company. Grohe also had an impressive 25-year career at Dell EMC, finishing as VP and GM with a focus on the global flash business.
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With over three decades in the SaaS and storage industry, Grohe has deep experience and possesses a rare dedication and passion for winning that is based on a customer-centric perspective. In addition to his roles at major tech companies, Grohe is an advisor and board member of many Silicon Valley fast-rising companies.
WekaIO saw 600% revenue growth in 2019 and continues to accelerate its growth in 2020. This meteoric trajectory is fueled by a unique ability to impact businesses by helping them to modernize AI workflows with software-defined storage systems optimized for NVMe and the hybrid cloud. Weka empowers companies to solve the most difficult IT infrastructure problems so they can extract maximum value from their data and expedite time-to-market. WekaFS™, the world’s fastest parallel file system and Weka’s flagship product, maximizes CPU and GPU performance and ROI by eliminating I/O bottlenecks to accelerate the data-intensive applications commonly found in artificial intelligence (AI), machine learning (ML), deep learning, life sciences, and financial analytics.
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