Open every clip before it goes anywhere. When an agent searches your footage, it hands back its own summary of what it found. That summary tells you where to look, but it doesn't show you the clip. Review in two passes. First, confirm each clip shows or says what the summary claims. Then set the start and end points yourself, because search results rarely begin and end where an edit would. Keep a short note of what you rejected and why, so the next search can be worded better.
Why the agent's summary isn't the review
An AI assistant working through a search tool only sees what the tool returned, usually a file, a time range and sometimes a reason. It then writes about those results in confident prose, whether the match is exact or loose. When the tool's reason paraphrases speech or on-screen text, the agent is paraphrasing a paraphrase. Nothing in that chain is exactly wrong, but you can't cut from a paraphrase. The review starts when you watch the moment.
What goes wrong in agent-found clips
The most common problem is the near miss. Ask for someone talking about nerves before a performance and you might get a performer saying it took years to relax on stage. That's related, and it might even be the better clip. But it's a judgment about your piece, and the agent can't make it for you.
Next is the whole-file hit. When the footage is a set of short videos, a quick search can return entire videos as candidates and leave the actual moment somewhere inside. The agent reports a find, and you still have to scrub.
Then there are boundaries. A result that lands on a single line or a brief visual tends to be tight, and most need some room added before and after.
Last, the agent can only report what came back. If a clip you remember isn't on the list, that tells you nothing about whether it exists.
Where the clips came from changes the review
How much checking you need depends on the route the agent used.
If you pasted clips or frames into the chat yourself, you've already watched them, so you're mostly reviewing the agent's notes.
If the agent reached your files through a filesystem connector, it saw filenames and folders, and nothing of the picture or sound. A "found" clip means the name matched, so you have to open each file from the start.
If your team built its own pipeline of transcripts and a vector store, results come back as transcript chunks with timestamps. You check that the words match and that the timestamps line up with the video. Anything that is only visual was never searchable in the first place. Working from transcripts goes further into that route.
A hosted video search connector returns time ranges from footage it has indexed, often with a reason for each. There's less scrubbing, but near misses still happen.
Check an agent's picks before they reach the edit
Vivu connects to any assistant that supports MCP, such as Claude or ChatGPT. Once footage is uploaded to a Vivu project and indexed, you can ask the assistant to find the part where the host admits being nervous before a show. When the precise search finishes, you get a few time ranges, each with a one-line reason. Use the reasons to decide what to open, and do the real review on the result page, which previews the segments one after another. The result page link expires after four hours, so review in one sitting, select the ranges you're keeping, and choose Export original clip to prepare the source footage for download. A fast search comes back sooner, but on short videos it can return whole files in place of the moment, so it's better for checking whether anything relevant exists than for review.
Send the exported clips to whoever cuts the piece, with your note on the near misses you set aside. Handing a selects list to an editor covers that step in more detail.
This route has limits. Each search stays inside one project, footage has to be uploaded and indexed in the cloud before you can search it, searches draw on a plan allowance (there's a free tier and paid tiers, with limits listed on Vivu's pricing page), and results are time ranges you open, not frame-exact timestamps. If your footage can't leave your own storage, or a review needs exact frames, one of the other routes fits better.
When you don't need a formal review
If the agent found one clip in a file you know well, watch it and move on. If the clip only answers an internal question like "did we ever cover this topic?", a glance at the reasons may be enough. The two-pass review matters when the clip goes into something published, or when someone else will cut from it.
How much to trust the list
It depends on what the clip is for. A list that only tells you whether something exists can be taken more or less on trust. A list someone will cut from needs every clip opened and trimmed by a person who knows what the piece needs, whichever route found it.
FAQ
Can I ask the AI agent to review the clips for me?
Partly. It can compare its reasons against your request and flag the ones that look indirect. But it's working from the same text it already gave you and hasn't watched the clips the way you will. The final pass is still yours.
Why does the clip start in the middle of a sentence?
Search results mark where the match is, and a match on one line or a brief moment is usually tight. Add a little time before and after when you trim. If the clip opens on a setup line like "here's what to do" and the point comes later, extend it forward.
The agent found nothing. Does that mean the footage isn't there?
No. An empty result can mean the moment isn't in the footage, or that the request was too narrow. Loosen the description by dropping the camera angle, or describe the scene instead of the exact line, and search again before you conclude it doesn't exist.
Should I trust numbers or quotes in the agent's summary?
Treat them as pointers. A summary that paraphrases on-screen text or speech can be close without being exact. Check any number, name or quote against the original clip before it goes into a script or deck.