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Higher Education Company Consolidating SharePoint and AI-powered tagging
Company Situation
The company is a mid-sized accredited higher education institution with a focus on theological studies. Their team includes approximately 75 full-time staff and around 530 students, with a core group of roughly 15 to 20 academic staff who actively engage with archival media content. The institution manages a significant digital archive containing approximately 8 terabytes of video content originating from a notable founder’s past sermons and teachings.
Existing Workflow
Currently, the institution stores its media assets in SharePoint, inherited from a previous partnership with a third-party digital library provider whose services have since lapsed. Students and faculty access to these archives is limited, and search capabilities are rudimentary, requiring knowledge of file names or folder structures. The institution also works with an external media partner who creates sub-clipped, bite-sized video content to supplement the archive. Historically, the institution maintained a public-facing website for media access, but this is no longer in place.
Issues with the Existing Workflow
Poor searchability and accessibility: Content is difficult to find without prior knowledge of file naming conventions or folder locations.
Manual tagging burden: The lack of automated metadata tagging means significant manual effort is required to organize and make content discoverable.
Limited user experience: Students and faculty cannot easily search or interact with the content in a natural, intuitive way.
Infrastructure constraints: The institution prefers a cloud-based, web-accessible system to avoid costly server investments and reduce IT overhead.
Uncertainty around user licensing: Large student numbers pose questions about access scalability, while active users are a smaller subset of staff and faculty.
How Shade Would Change Their Workflow
Shade offers an AI-powered, cloud-first media asset management solution that would transform how the institution organizes, searches, and distributes archival video content. Key improvements include:
- Automated AI tagging and metadata generation, eliminating manual tagging and enhancing discoverability.
- A video-first platform designed for natural language search, enabling users to find content through intuitive queries rather than file names.
- Cloud-mounted drives that allow editors to work directly with footage without local downloads, saving time and storage.
- Built-in review and approval workflows to facilitate collaboration among academic staff and media partners.
- Flexible licensing with free guest access, enabling students to search and view content without incurring additional licensing costs.
- Web-based access that removes the need for local infrastructure investments, fitting the institution’s budget and IT capabilities.
Benefits
- Significant reduction in manual effort through AI-driven tagging and indexing.
- Improved accessibility and search experience for students and faculty.
- Scalable user access model accommodating both staff and students efficiently.
- Time savings for media editors via cloud-mounted streaming.
- Enhanced collaboration with integrated review and approval tools.
- Cost-effective, cloud-native deployment suited to budget-conscious educational institutions.
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