Challenge
A major broadcasting company had over 10 million hours of archived content that was difficult to search and monetize. Manual tagging was slow and expensive, limiting content discoverability.
Solution
We deployed an AI-powered media intelligence platform that automatically analyzes video content, generates metadata, identifies speakers, and creates searchable transcripts. The system uses NLP and computer vision to understand content at scale.
Results
- 10M+ hours of content automatically indexed
- 80% reduction in content tagging time
- 5x increase in content reuse
- 35% increase in archive monetization
Technologies Used
Natural Language Processing, Speech Recognition, Computer Vision, Automated Transcription