Start with what you remember about the moment, because that decides the method. If you remember a line that was said, search a transcript and jump to the timecode it gives you. If you remember something you saw, a transcript will not help, and you are choosing between scrubbing the file yourself and searching it by describing the shot. The moment nothing can find is the one you cannot describe either way.
If you remember something that was said
Transcribe the file and search the text. Automatic captions on most video platforms, the speech-to-text built into editing software, and open-source transcription you can run on your own machine all produce a transcript with timecodes, and most editing timelines let you click a word and land on that part of the video. For spoken moments this is the cheapest reliable route there is. It fails when the words you remember are not the words that were said, when a name came back misspelled, and in the much larger case where the thing you want never had any audio attached to it. Searching by what was said goes further into that route.
If you remember something you saw
This is the harder half of the question. People who shoot a lot try to solve it while the camera is still running, by marking the moments they like as they happen, which works until the day they forget to. After the fact, the baseline is scrubbing: open the file, drag, watch, drag again, and usually go past it twice before you land.
The other route is to describe the shot and let software look for it. The video goes into a search layer, gets read once, and then you type something like "a phone lock screen showing the time and notifications" and get back places to check. Vivu works this way: you put the recording in, describe the moment, and get back time ranges to open instead of a list of keyword hits. The range you keep exports as the original clip, which matters if the reason you were looking is that somebody else has to cut it. How that reading actually works is worth knowing before you trust the results.
What comes back depends on how hard you ask
Description-based search usually has a quick mode and a precise mode, and they answer different questions. The quick mode tends to hand back whole files that look relevant, with no pointer to where inside them the thing appears, so on a long recording it mostly confirms that your memory was right. The precise mode on the same query comes back with short ranges and a line of reasoning for each one, and it narrows to the part of the file where the thing is actually on screen. It also has to run to the end before it shows you anything, so you wait once instead of scrubbing continuously.
The fastest route is the one that matches your memory
"Fastest" is decided by what you have, not by the tool. A remembered sentence goes to the transcript, and that is minutes of work with tools you probably already own. A remembered image goes to the quick pass first, to find out which file or which stretch of file you care about, and then to the precise pass to land on the range. Running them in that order is a practical habit rather than a measured result, and the reason is that the precise pass costs more and is worth spending once you know the moment is really in there. If what you are after is a moment worth cutting rather than a moment you specifically remember, that is a different job, and pulling highlights out of a long recording is the version of it.
When you don't need any of this
If the file is short, or you shot it this week, or the moment sits somewhere predictable like the opening or the start of the Q&A, open it and drag. The same goes if you kept notes or chapter markers while recording. A note written by the person who was in the room beats every search tool, because it already contains the judgment. Search becomes worth the setup when the recording is long enough that you cannot hold its shape in your head, or when there are enough recordings that you no longer know which one the moment is in.
So the question to settle before you start looking is whether you can say the sentence or describe the frame. If you can say the sentence, a transcript gets you there today. If you can only describe the frame, you are choosing between your own patience and a search layer you have to put the video into first, and how often this happens to you decides which one is cheaper. Once a quarter, drag the playhead. Once a week, that is not a workflow.
FAQ
Can AI find a specific moment in a video?
Yes, inside limits that matter. Software can find a moment you can describe, either as words that were spoken or as something visible on screen, and what it returns is places to look that you still confirm yourself. It cannot find a moment defined by something it has no way to perceive, like which take the director preferred. What comes back is a time range to open, not a frame-accurate cut, so the last step is always a person watching.
Why did my search return the whole video instead of the moment?
Because quick search modes answer a different question: which files are worth opening. On a set of short clips that is close to the whole answer, since the file almost is the moment. On a two-hour recording it leaves you scrubbing. If you need the actual range, run the slower precise mode on the same query and expect to wait for the job to finish before anything appears.
Can I search a video without uploading it anywhere?
For spoken words, yes. Transcription can run on your own machine and gives you a searchable text file with timecodes without the video leaving the building. Searching by what the footage looks like is different: that requires the video to be read and indexed by a service, so the file has to be uploaded there first. If the footage cannot leave your machine, transcript search plus scrubbing is the honest limit of what you have.
What if nobody says anything in the moment I am looking for?
Then transcripts are out and you are down to scrubbing or description-based search. A product shot, a reaction, someone walking through a doorway: these exist only in the picture, so whatever you use has to be looking at the picture. This is why transcript search feels like it solved the problem right up until the week it does not.