The example projects on this page utilize the TwelveLabs Video Understanding Platform to enhance and streamline content creation workflows.

Lit(m)

Summary: Lit(m) is an automated system designed to capture concert experiences by recording live footage, identifying iconic moments, and automatically posting highlight clips to Instagram Stories.

Description: The platform utilizes the Marengo 2.7 video understanding model for lyric-based video searches. It creates dynamic indexes for each video and employs advanced text-to-timestamp matching for accurate clip extraction. This end-to-end automation solution seamlessly combines concert recording with social media posting by integrating multiple APIs, including OpenAI, Instagram, and Twilio.

GitHub repo: samanthavmac/litm

Devpost: Lit(m)

TrailMixer

Summary: TrailMixer is an AI-powered video editor that automatically creates polished trailers from raw footage by intelligently selecting clips and matching music based on sentiment.

Description: The system incorporates advanced TwelveLabs integration, utilizing sophisticated prompts with mathematical constraints for precise trailer generation. It also features comprehensive upload, indexing, and analysis pipelines. This creative automation tool meets the promotional content creation needs of event organizers, filmmakers, and content creators, significantly reducing manual video editing time from hours to mere minutes.

GitHub repo: xrhuang10/trailmixer, prestonty/Trailmixer-frontend

Devpost: TrailMixer

Thirteen Labs

Summary: Thirteen Labs automatically transforms any video into interactive 3D experiences by converting video content into live, animated 3D models that are fully rendered in the browser.

Description: The application utilizes the TwelveLabs API for comprehensive video analysis, including object detection, motion analysis, and multi-perspective queries, specifically designed for Three.js 3D generation. This groundbreaking application showcases a novel use of video AI for 3D reconstruction, combining TwelveLabs analysis with Gemini 3D code generation and real-time visualization in the browser to create truly innovative content creation workflows.

GitHub repo: Marcus990/ThirteenLabs

Devpost: Thirteen Labs

Weaver

Summary: Weaver automatically generates personalized Spotify playlists based on the mood and emotional tone of uploaded videos, effectively connecting melodies to visual experiences.

Description: The application utilizes the TwelveLabs API as its primary workflow driver for video indexing, task monitoring, and gist generation, which helps extract titles, topics, and hashtags that inform the music selection algorithms. This innovative platform bridges video AI and music curation by integrating the TwelveLabs, Google Gemini, and Spotify APIs to create mood-matched soundtracks for content creators and personal users.

GitHub repo: anthonytoyco/weaver

Devpost: Weaver