Why Video Search Is Broken (And How We're Fixing It)

You can search the internet in 200 milliseconds, find any email you have sent, and locate a single line in a million-file codebase.

Finding the moment someone said "let's go with take three" in yesterday's shoot still means scrubbing through hours of footage.

The problem is metadata

Video files are opaque to the operating system. A 40 GB R3D file and a 200 MB MP4 both show a filename, a duration and a thumbnail.

Text is searchable by nature. Video is not. Storage got cheaper and shooting ratios grew, and the average production now generates 20 to 50 times more footage than it uses.

Current approaches

Folder structures and naming conventions break down once more than one person is involved. Was it in B-Roll/Day2 or Selects/Interview_Final_v2?

NLE markers and bins help during the edit and stay locked inside the project file. You cannot search across projects.

Manual logging works with the budget for an assistant editor to spend hours on it. Most teams do not have that.

Footage that indexes itself

When you process a video, FrameQuery builds a local index that holds:

• Transcription: every word, with timestamps
• Object detection: what appears on screen, frame by frame
• Face recognition: who is in each shot
• Scene descriptions: AI-generated summaries of what is happening

The index lives on your machine. Searching it is instant and free. Type "Lena product reveal" and get timestamped results across the library, ranked like a search engine.

Hybrid by design

Frames and audio are extracted on your device, sent for analysis and discarded. The search index, face recognition and voice recognition stay local. The index works offline, and it would keep working if FrameQuery disappeared tomorrow.

Indexing happens in the cloud and is what you pay for. The resulting index is saved locally and search is always free.

Next

We are in early access. Download FrameQuery for priority access and locked-in pricing.