Vizrt launches AI-powered advances for speed and accuracy in media management

Vizrt has released Viz One 8.1, an upgraded media asset management platform powered by AI to help broadcasters and content owners manage growing volumes of content with greater speed and accuracy. By integrating aiconix’s DeepVA AI technology, the system now automates tasks like shot logging, tagging, and archive research, reducing manual work and making relevant content easier to find within seconds. The AI-driven visual recognition can identify faces, objects, and scenes, delivering up to 50% higher logging accuracy and significantly faster workflows. With secure deployment across on-prem, hybrid, and cloud setups, Viz One 8.1 gives media teams a smarter, scalable way to improve efficiency, boost content reuse, and accelerate production across news, sports, and entertainment. Vizrt, the leader in live production technology revolutionizing viewer engagement and experience, releases AI-driven advances focusing on speed, intelligence, and accuracy in the industry-leading media asset management (MAM) system, Viz One 8.1. Broadcasters and content owners today face mounting pressure to deliver more content, faster, and across more platforms. With the ever-growing volume of raw footage and the limits of manual shot logging and archive research, traditional workflows are no longer sustainable. To address these common challenges, Viz One 8.1 integrates with aiconix’s DeepVA sovereign AI platform, automating key stages of media management and moving teams from time-consuming manual processes to managing media with speed and accuracy. Enrich your content with visual understanding With the integration, the AI-powered visual recognition in Viz One 8.1 means the user can surface the right content in seconds. It adds visual understanding to archives and workflows, automatically identifying and tagging faces, objects, and scenes within video material, including through trainable custom models. The AI automated metadata generation replaces the need for manual logging. Instead, teams can review metadata logged by AI, train custom models for unknown entities, and perform optional quality assurance reviews. The strength in reliability is significant: up to a 50% increase in logging accuracy, 10 times the speed in logging workflows, and five times quicker search and discovery. With the increase in time efficiency, surfacing the best clips, scenes, and themes dramatically expands the possibilities for reuse, compliance, and even monetization of the content. “Content creators need AI that works for their specific needs, not a one-size-fits-all solution,” says Esther Arroyo, CMO at aiconix. “DeepVA’s ability to train custom models and generate structured, machine-readable metadata ensures Viz One customers can optimize their workflows and deliver more relevant, localized content to their audiences.” Faster research and clip discovery mean fewer bottlenecks and greater creative flexibility for broadcasters and content creators working across news, sports, and entertainment on any platform. Built on a future-ready foundation Viz One 8.1 builds on the system’s containerized architecture designed to scale seamlessly across on-premises, hybrid, and cloud environments. DeepVA’s AI services are deployed securely within each Viz One environment, providing powerful AI workflows without risking sensitive data leaving the infrastructure. Together, Vizrt and DeepVA pioneer a pragmatic approach to AI in media: delivering automation where it adds real value, without unnecessary complexity. Viz One 8.1 delivers the kind of AI that makes a measurable difference; saving hours of manual tagging, surfacing the most relevant assets instantly, and helping content creators tell better stories, faster. “Viz One 8.1 is the next step in our long-term vision to accelerate efficiencies,” says Jochen Bergdolt, Head of MAM at Vizrt. “By combining Viz One’s proven reliability with intelligent automation, we’re giving customers the tools to work smarter today – and build stronger media operations for tomorrow.”