How to Build a Searchable Video Library From Scratch

A "searchable video library" sounds like it requires a complex setup: a DAM platform, rigid naming conventions, an army of interns with spreadsheets. It does not. If you can mount a drive and click a button, you can build a searchable library from footage you already have, in whatever state it is already in.

This guide walks through the process from storage decisions to your first search query.

Step 1: Choose where your footage lives

FrameQuery reads footage from wherever it already exists. You do not need to move, copy, or re-organize files. But understanding your storage options matters for access and performance.

Local drives. Fastest access. If your footage fits on an internal SSD or a fast external drive, this is the simplest setup. Playback is instant and there is no network dependency.

External drives. Most editors accumulate USB and Thunderbolt drives over time. FrameQuery can index footage across multiple external drives. The search index works even when a drive is disconnected, so you can search your full library and reconnect the relevant drive only when you need to play back a specific clip.

NAS (network attached storage). Good for teams or large archives. FrameQuery can scan network volumes the same way it scans local folders. Performance depends on your network speed, but since the search index is local, only playback requires the network connection.

The key point: you do not need to consolidate. If your footage is split across three external drives and a NAS, that is fine. Add all of them as source folders and FrameQuery builds a single unified search index across everything.

Step 2: Point FrameQuery at your folders

Open FrameQuery and add your media source folders. You can add a top-level directory like /Volumes/MediaDrive or something more specific like /Volumes/MediaDrive/2025 Projects. The application scans recursively, so pointing at a top-level folder captures everything inside it.

Auto-scan detects new files added to these folders automatically. Drop a new camera card dump into your media drive and FrameQuery picks it up without any manual intervention.

FrameQuery supports over 50 video formats natively, including R3D, BRAW, ProRes, DNxHR, XAVC, MXF, CinemaDNG, and common formats like MP4 and MOV. You do not need to transcode before adding footage.

Step 3: Process your footage

Processing is the step that turns raw video files into searchable data. FrameQuery's processing pipeline runs four analysis passes on each clip:

• Transcription extracts spoken words with word-level timestamps and speaker diarization.
• Object detection identifies objects visible in each frame.
• Scene description generates natural-language captions of the visual content.
• Face and voice recognition clusters people across your library (this runs locally on your device).

Processing takes roughly five minutes per hour of footage. You do not need to process everything at once. Start with the projects you are actively working on and add older footage when it is convenient.

Once processed, every transcript, object label, scene description, and face cluster is stored in a local Tantivy search index on your machine. This is what makes searching fast and offline-capable.

Step 4: Search

With footage processed, your library is searchable. Here is what "searchable" actually means in practice:

By dialogue. Type a phrase someone said and find the exact moment they said it. "We need to revisit the budget" lands you on the timecode where those words were spoken.

By visible objects. Search for "laptop" or "staircase" or "dog" and find clips where those objects appear, including footage with no dialogue at all.

By scene content. Describe what you are looking for in natural language: "person walking through a warehouse," "close-up of hands on a keyboard." Scene descriptions match the visual context of your footage.

By person. Once FrameQuery clusters faces across your library, you can search for a specific person and find every clip where they appear, across every project and shoot.

You can combine these modalities in a single query. "Sarah talking about the prototype" can match across face recognition, transcript data, and object detection simultaneously.

Practical advice on folder structure

You do not need a specific folder structure for FrameQuery to work. The search index is built from the content of the videos, not their filenames or folder paths. That said, a sensible folder structure still helps when you need to browse rather than search.

A common pattern that works well:

/Media
  /2025
    /ProjectName
      /Camera Originals
      /Audio
      /Exports
  /2026
    /ProjectName
      ...

The structure gives you a browsable hierarchy by year and project while keeping camera originals separated from exports and renders. But even if your current structure is a flat folder of 5,000 clips with camera-generated filenames, FrameQuery can still index and search all of it.

Handling multiple drives

If your footage spans multiple drives, add each one as a separate source folder. FrameQuery builds a single search index across all of them. When you search, results come from every drive, with the source path visible so you know which drive to connect.

The search index is stored locally on your boot drive, separate from the footage. This means you can search your full library even when some drives are disconnected. You only need the physical drive connected when you want to play back or export a specific clip.

What "searchable" really means

A searchable library is one where you can start from a question and arrive at a clip. Not "browse until you recognize something." Not "ask the person who was on set that day." You type what you need and the tool finds it.

That is a fundamentally different relationship with your footage. Instead of dreading the prospect of digging through old projects for B-roll, you search for it the same way you would search your email. The footage is already organized by its content. You just need to ask.

Join the waitlist to build your searchable video library when FrameQuery launches.