✨Video training hub

Your insights help shape our model.

AI automontages and semantic video search are revolutionizing how we create, discover, and interact with video content. AI automontages leverage advanced machine learning, computer vision, and natural language processing to automatically identify and compile the most compelling moments from hours of raw footage eliminating the need for tedious manual editing and empowering creators of all skill levels to produce polished, shareable videos in minutes.

HELP’s advanced video model identifies the best moments, such as kills, victories, or exciting highlights, saving countless hours of manual editing. These specialized models streamline the process of finding viral-worthy content from Fortnite videos, making it easier for players to create engaging social media posts.

Meanwhile, semantic video search transforms content discovery by enabling users to find specific moments within videos based on meaning and context rather than just keywords; you can search for “the part where they talk about black holes” or “customer complaint,” and the AI will instantly surface the relevant segment even if those exact words never appear. Together, these technologies unlock a new era of video storytelling and navigation: creators can rapidly generate engaging content, and audiences can instantly access the moments that matter most, making video libraries more accessible, interactive, and valuable than ever before.

The HELP annotation hub provides a way for people to join as annotators, rewarding their contributions with points. Our tool is designed to be as user-friendly as possible. The annotation hub offers a simple and rewarding way for you to contribute to the HELP DAO. Annotators earn points while providing metadata corrections. To ensure data quality, each video undergoes multiple verifications. Our model identifies kills and other important actions, and you can help us train it. Video meaning analysis undergoes fine-grained understanding to extract detailed insights from each scene. The system can grasp the best moments across different scenes rather than just static emotional snapshots.