Video Search
Semantic Video Search, Explained
Semantic video search lets you find a moment in your footage by describing it in plain language, instead of scrubbing a timeline. Here's how it works and why it matters for editing.
What semantic search means for video
Traditional footage search is keyword or filename search: you find a clip if it's labeled correctly. Semantic video search indexes what's actually happening in each frame — objects, actions, dialogue, on-screen context — so you can search your footage the way you'd search text: "the moment she picks up the microphone," not "clip_047.mp4."
Why this matters for editing speed
The slowest part of editing raw footage is usually finding the right moment across hours of unlabeled clips. When every frame is indexed and searchable by meaning, an editor — human or AI — can go straight to the moments that match a story, instead of scrubbing linearly through everything shot that day.
This is also what makes agentic video editing possible in the first place: an AI editor can only build a story from raw footage if it can find the relevant moments in that footage first. Semantic search is the retrieval layer underneath the editorial decisions.
How Broll uses it
Broll watches and indexes every frame of your raw footage on import, so both the agent and, eventually, you can search it like text — surfacing the best takes, finding footage that matches a specific beat in the story, and placing the right clip in the right place without manual logging.