Videon receives $9 million boost to deepen its edge computing streaming business

Voyager Capital、 Fortson VC, Bruce Chizen and Cercano Management have decided to invest $9 million in Videon to further develop solutions that enhance its edge computing video platform.

This boost brings the total investment in the Videon solutions over the past seven months to $16.3 million. Industry companies such as Techex、 Theo Technologies、 V-Nova そして Zixi are already building and deploying applications that leverage the Videon edge computing capabilities for their customers.

Tricia Iboshi, CEO of Videon, welcomes the benefits this round of funding will bring to the company: “We’ve spent the last 6 months working with industry leaders across the video ecosystem to unlock the potential of the edge to deliver new experiences, drive greater efficiencies, and create more opportunities for personalization and monetization. The latest funding will enable us to continue to innovate, adding more video applications, enabling disruptive workflows and driving live video at scale.”

In parallel, Louis Toth, managing partner at Alter Venture Partners, highlights the latest developments promoted by Videon: “Videon is revolutionizing live video through powerful edge processing at an unrivaled price point. Videon’s video edge computing platform has huge market potential — it opens up unlimited live video use cases across sectors powered by low latency, multiple camera angles, technologies like AI and Machine Learning, and new monetization opportunities.”

Edge Computing at Videon

Videon places edge computing-based processing at the point where video is created, enabling a huge variety of video processing tasks to be completed before the content moves to the cloud. This allows users, according to the company itself, to significantly reduce the complexity and cost of live production, adding multiple camera angles and remote feeds to meet growing audience expectations for personalised content. For Videon, processing video at source “is the key” to reducing latency。

Recently, a leading global sports analytics platform deployed the Videon edge computing video platform on-premises, running custom Python scripts, Docker containers and a full set of coding and packaging. According to Videon itself, this enabled the company to reduce its cloud processing costs while achieving a significant reduction in latency.