Yes, and for a single file you can do it in the next ten minutes for free. The word "inside" is doing a lot of work, though. A video holds the words people said and the things visible on screen, and those two are reached by completely different machinery. Most products that answer "yes, you can search video" mean the first one: they transcribe the audio and search the text. If what you are looking for was never spoken out loud, that kind of search cannot see it.
What you are actually searching
Speech is the easy layer. Transcription is mature, a transcript is a text file, and text search is a solved problem. Anything said in the video is findable this way, down to the timecode where it was said. Word search over spoken audio is the route most people already have without buying anything.
The picture is the hard layer. A product shot, a gesture, a sign in the background, a lock screen with the time on it: none of that is in the transcript, and reaching it means something has to look at the frames and describe them. That is a different class of system, and what it does to the frames explains why it costs more to run.
One file or a few hundred hours
Scale decides this more than features do. With one video, open it and use the player. Arrow keys, the caption or transcript panel, and your own eyes will beat any purchase. With a few dozen, transcribing everything into text files and searching the folder is a weekend of setup that pays off for years. Once an archive runs into hundreds of hours, the manual methods quietly fail, because the cost is no longer the search. It is deciding which file to open first.
The routes, and what each asks of you
Transcribe and grep is the cheapest serious option. You run each video through a speech-to-text tool, keep the text next to the media, and search it like any other document. The work is in the plumbing: naming, keeping transcripts in sync when you re-export, and accepting that silent footage is invisible. Getting a clean transcript out of a video file is the first step.
Building the visual half yourself is a real project. Sample frames, generate embeddings, put them in a vector store, write a query path. Teams with engineers do this and get exactly what they specified. It is weeks rather than an afternoon, and somebody owns it afterwards.
Uploading into a retrieval layer buys the visual half instead of building it. The video is indexed once when it goes in, and from then on you ask in plain language and get back time ranges you can open, each with a line about why it matched.
Keyword or meaning
This is the distinction that decides whether transcript search is enough for you. Text search needs your words to be the words that were said. Someone describing nerves before a performance may never use the phrase "stage fright", so searching the phrase returns nothing while the moment sits there in the footage.
A search that works on meaning handles the paraphrase. Ask for a moment where somebody admits to being nervous before going on stage, and what comes back is a set of time ranges from several different videos: a passage from an interview where it is the topic, and an aside in the middle of a performance where it is one sentence. Vivu answers that way inside one project, and it also hands back the near misses, like a passage about how it took years to get comfortable on stage, which is related if you squint. Ruling on those stays your job.
When you do not need this
If the answer lives in one video you shot yesterday, none of this applies. If you go looking through your footage once a month, a folder of transcripts is enough and will stay enough. And if what you want is a finished cut, search is the wrong purchase: finding the segment and assembling it are separate jobs, and the tools that find things do not edit them.
How to tell which one you need
Write down the last three things you went looking for in your own footage. If all of them were said out loud, you need transcripts and a search box over them, and you can stop reading comparison pages. If any of them were visual, no amount of transcript tooling will reach them, and the real question becomes how often that happens and how long you currently spend scrubbing. That number, weighed against the cost of building the visual half or renting it, is the whole decision.
FAQ
Can you search inside a video without uploading it anywhere?
For one file on your own machine, yes. Transcribe it locally, keep the transcript next to the video, and search the text; many players also search captions directly. What you cannot do locally is the visual half, because the systems that search the picture index the video in the cloud, which means the file goes up first. So the no-upload version of this is real but limited to the words.
Can I search a video that has no captions or transcript?
Yes, in two ways. You can generate a transcript yourself from the audio, which takes one pass per file and turns the spoken content into searchable text. Or you can use a search layer that indexes the picture, which is the only option when the thing you want was never said out loud. Missing captions are not a blocker either way; silence is.
Why does transcript search miss things I am sure were said?
Usually because the transcript has the words slightly wrong, or because you are searching for a phrasing nobody used. Names, jargon, crosstalk and background noise all produce near misses in the text, and a near miss is invisible to exact search. Try a shorter fragment, search a distinctive single word rather than a sentence, and read the transcript around the timecodes where the topic is likely to be.
Can I search across a lot of videos at once, or only one at a time?
In practice you search one collection at a time. Tools that index video group it into libraries or projects, and a query runs inside one group, so answering a question across everything you own means running the same search group by group. It is worth deciding up front which videos belong together, because that grouping is what you will be searching for a long time afterwards.