Masters of Scale | Cody Coleman’s entrepreneurial journey: From QuestBridge scholar to Coactive AI

What you’ll learn from this webinar

Consider a global streaming platform or national media company aiming to personalize content for its users. With Coactive Dynamic Tags, you can quickly assign moods to each video. For example, you might search "Trolls" for scenes that are  "brainy.” When Coactive returns the results, you can automatically apply the “brainy” tag to all relevant clips. This precise tagging delivers highly relevant content recommendations.  As this feature matures, we expect it could be used in the following ways:

• Create cut sheets: _{Quickly generate summaries and highlight reels by identifying key moments in your videos minute-by-minute. This means you can put together summaries that capture all the exciting parts without spending hours watching and cutting videos.}
• Assign advertisement tags: _{Categorize videos with relevant advertising tags to optimize targeted marketing campaigns. This helps advertisers place their ads more effectively, ensuring they reach the viewers most likely to be interested.}
• Personalized content recommendations: _{Tailor viewing experiences by automatically tagging videos with moods or themes. This makes movie night a lot more engaging by helping your platform show users videos that match their preferences, making them more likely to stick around and watch more content.}
• Identify spoken languages: _{Automatically detect and tag the languages spoken in different segments of your videos. This helps you manage and deliver your multilingual content better and ensures users always find the right shows or movies by language. You can see how easy it is to identify Portuguese and Italian in seconds.}
• Metadata enrichment: _{Use multimodal AI to add detailed, context-specific metadata to videos for improved searchability and asset management. No need to wait for humans to watch every minute of footage and manually add metadata. You can see how easy it is to add metadata based on the mood of the movie.}