Partly, and the caveat is the whole answer. Several tools will take a six-hour VOD and hand back a set of ranked candidate clips without you touching the timeline. What none of them can do is know what counts as a highlight on your channel, so the realistic outcome is that the software cuts six hours down to twenty candidates and you watch the twenty. That is a real saving. It is not the thing the marketing implies, which is that you get finished clips while you sleep.
Worth knowing what the detection is actually keying on before you judge whether it will work for you.
What the automatic detection looks at
Most highlight detectors combine a few signals. Chat message rate is the strongest one on Twitch, because a live audience reacting is genuinely informative. Audio energy catches shouting, laughter, and sudden silence. The transcript supplies keywords. Some tools add scene or face detection, and game-specific ones read the HUD for kills, wins, and deaths.
None of that is a model of quality. It is a model of where something loud happened, which happens to overlap with highlights for a large slice of streaming content.
Where it works well
Fast gameplay with an active chat is close to the ideal case. The signals are dense, the moments are short, and the boundaries are clean, so the clip that comes back usually needs a few seconds trimmed at most. If you stream competitive games to a chat that spams when something goes wrong, the automatic route will find most of what you would have found yourself.
Where it falls apart
Small chat means no signal. A stream with thirty concurrent viewers does not generate the message spikes these systems are built to read, and the output degrades into audio-peak detection.
Talking content is the other weak spot. Just-chatting streams, tutorials, and interviews carry their value in quiet stretches, and a detector tuned on reaction footage skips them. The related failure is boundary detection: a callback that only lands because of a setup forty minutes earlier gets cut as a naked punchline, and a good explanation gets clipped starting halfway through the sentence.
There is also the workflow cost nobody mentions. Producers who have tried this report that the bottleneck moves rather than disappears, from finding to reviewing. You still sit through every candidate to reject most of them, and for a back catalogue you pay that review cost per file, forever.
The version of the question that works better
Automatic highlight detection asks the machine to have taste. Asking for a specific moment does not, and it turns out most clipping needs are the second kind: the part where you reacted to the patch notes, the run where the boss fight went sideways, the answer you gave about your setup.
That is the ask a retrieval layer answers. You describe the moment, it returns where in the VOD it happens along with the surrounding context, and the cutting stays your job. Vivu works this way and does not edit or generate anything, which makes it useless if your problem is producing the vertical version, and useful if your problem is knowing which four minutes to send to your editor.
When you should not automate this
If you clip a handful of moments a month, the setup time for any of these tools exceeds what they save you. Hit the clip button while you stream and be done.
If the highlights are the reason people watch you, be careful about outsourcing the judgment at all. Channels with a specific sense of humour tend to find that the automatic candidates are technically correct and tonally wrong, and correcting that costs more attention than choosing from scratch.
And if you have never actually measured the time, measure it once before you buy anything. People are often surprised by which step is long.
How to decide
The question is not whether AI can find highlights in a VOD. It can find events, and events are a decent proxy for highlights in loud content. The question is whether your highlights are events.
If they are, run a detector and take the twenty candidates. If they are not, an automatic pass will keep handing you plausible clips that are not yours, and you are better off making the archive answer direct questions instead of asking it to guess.