RADCOM Reveals CEO Transition

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RADCOM Ltd. has announced that the Board has appointed Hilik Itman as interim CEO, effective April 7, 2024. Hilik, who has served as the Company’s Chief Operating Officer since 2020, brings 27 years of invaluable experience with Radcom, having held various key roles in R&D and serving as Vice President of Research and Development since 2014. Guy Shemesh, who assumed the CEO role in mid-February, is stepping down, effective April 7, 2024, due to personal reasons.

The board has initiated a thorough search process for a permanent CEO to lead the company into the next phase of its growth and transformation journey.

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Heli (Rachel) Bennun, RADCOM’s Executive Chairman of the Board, said: “I am pleased that Mr. Hilik Itman has agreed to serve as RADCOM’s interim CEO at the board’s request, and we extend our best wishes to Mr. Guy Shemesh. Mr. Hilik Itman has a proven track record in leadership roles at RADCOM, focusing on customer satisfaction for our installed base with our innovative assurance solutions.

“With my support, Hilik, the entire management team, and all the board members will ensure a seamless transition until we nominate a permanent CEO. I am confident that Hilik will navigate the Company successfully during this transition period, and we will continue to execute our business strategy effectively.”

Heli (Rachel) Bennun concluded: “RADCOM remains fully committed to enhancing profitability and growth, continuing the positive momentum of the past four years.”

RADCOM is an expert in 5G-ready cloud-native network intelligence solutions for telecom operators transitioning to 5G. RADCOM Network Intelligence consists of RADCOM Network Visibility, RADCOM Service Assurance, and RADCOM Network Insights. The RADCOM Network Intelligence suite offers intelligent, container-based, on-demand solutions to deliver network analysis from the RAN to the core for 5G assurance.

Utilizing automated and dynamic solutions with smart minimal data collection, on-demand troubleshooting, and cutting-edge techniques based on machine learning, these solutions work in harmony to provide operators with an understanding of the entire customer experience and allow them to troubleshoot network performance from a high to granular level while reducing storage costs and cloud resource utilization.


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