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Sports Media Company Streamlining Storage and Collaboration Workflows
Company Situation
The company operates in the sports media production sector, specializing in live event coverage and supplementary content creation such as B-roll and social media story pieces. Their small, remote team consists of approximately three to four video editors who handle footage primarily shot on high-end cameras like RED. The team supports dynamic, fast-paced sports environments—in this case, paintball events—and requires effective collaboration across different locations.
Existing Workflow
Currently, the company stores all footage on on-site RAID systems and backs up everything to Google Drive. Editors access media directly from drives for editing without a centralized media asset management (MAM) system. For company review, they rely on Frame.io, but only when external companies are involved. The workflow involves manual searching through raw clips, typically one to five minutes long, which are organized by editors but lack automated metadata or tagging.
Issues with the Existing Workflow
The primary challenge lies in efficiently searching and identifying specific content within large volumes of footage. Because paintball athletes don’t have easily recognizable faces on camera, editors rely on jersey numbers or unique playing styles to find relevant clips. This approach is not scalable and presents a steep learning curve for editors unfamiliar with the sport. Additionally, sharing and tagging content across multiple remote locations is cumbersome, with no centralized system to maintain consistent metadata or facilitate collaborative review and sharing.
How Shade Would Change Their Workflow
Shade’s integrated platform addresses these pain points by layering advanced AI-powered media management on top of existing cloud and streaming technologies. Using neural search and AI tagging, Shade can automatically detect jersey numbers and other relevant visual metadata, enabling editors to conduct natural language searches like “jersey number 12” to rapidly locate specific clips. This drastically reduces the manual effort required to sift through hours of footage. The platform also offers a collaborative MAM environment where media can be tagged once and shared seamlessly across locations, supporting live access without the need to download large files. Integrated sharing and review tools similar to Frame.io streamline the feedback process, while secure upload links allow external contributors to add content without accessing the entire workspace.
Benefits
- AI-driven tagging and neural search improve content discoverability, especially in challenging visual contexts such as sports footage.
- Centralized media catalog accessible remotely, enabling real-time streaming and collaboration without large downloads.
- Simplified sharing and review process with integrated commenting and version control.
- Reduced onboarding time for new editors unfamiliar with the sport through intuitive search and tagging.
- Secure, role-based access with easy upload capabilities for external collaborators.
Technologies Used
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