CASE STUDY became a cornerstone of the relationship , with VAST engineers collaborating directly with the NHL . systems to ensure content was flowing efficiently to the NHL HQ .
This successful collaboration led to an expanded relationship and the NHL moved its footage archive , consisting of over 20 petabytes of data , onto the VAST Data Platform . This decision not only ensured the longevity of their archival content but also set the stage for future AI-driven innovation . As Kennedy puts it : “ We have set ourselves up for future AI and machine learning workloads that will benefit the content generation business later down the line .”
After the successful archive implementation , the NHL turned to VAST to support their in-arena game footage content and data needs . The goal was to modernize and streamline the way game footage was captured and transferred from all 32 NHL arenas to NHL HQ in New York City .
“ VAST replication expands up to 36 sites and now each one of the 32 different NHL arenas sends digital content to a single platform . We ’ ve set the table to create a content platform that exists at the edge , where the game is being played ,” said Kennedy .
Enabled by the VAST DataSpace , this real-time replication significantly reduces the time it takes for game footage to become available for post-production and distribution among teams and media partners . This operational speed is critical for modern media workflows , where there is a high demand for quick turnaround times . With footage stored locally at each venue and made quickly available at the NHL HQ , editors and production teams in different locations can work on game highlights and other content without needing to be on-site .
“ We had great success with VAST in the past ,” Kennedy said .
“ So when we needed to replace storage in the arenas , we decided to future-proof ourselves by implementing VAST in all 32 arenas .”
In response to the NHL ’ s needs , the VAST Research and Development team tested this workflow and collaborated with the NHL on the rollout of all arena
Moving forward , the NHL is equipped to explore new content creation workflows that leverage data and footage directly from the arenas . With the required data capacity at each venue , the League can run real-time AI-driven workflows to generate highlights or unique content that wouldn ’ t be possible in a cloudbased solution .
Kennedy said : “ We can create a localized content generation engine by utilizing our exclusive camera
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