There is no single best one, because "AI DAM" covers at least four different capabilities sold under one label. The question that separates the options is plain: when someone on your team cannot find something, what do they type? Buy the system that answers that sentence well, and treat the rest of the demo as extra. Everything below is a way of pressuring that question until it gives you a shortlist.
What the AI in an AI DAM usually is
Four things, roughly. Automatic tagging of objects, faces and scenes. Speech transcription. Similarity search, where you hand it an example and ask for more like it. And cleanup of metadata on files already in the system.
Each fails in its own way. Tags are a fixed vocabulary somebody has to trust and keep alive. Transcription only reaches what was said, which leaves silent B-roll dark. Similarity search assumes you already have the example, which is not the situation you are in when you are looking.
The sentence test
Write down the last five things someone on your team went looking for and could not find. They tend to sound like "the bit where she explains why she left" or "the wide of the empty warehouse at dusk", and sometimes like a phrase somebody needs to locate across every transcript in a project. Now check what each candidate does with those sentences. Some hand back a list of files that match a keyword. Some hand back a place inside a file.
Vivu is built around the second answer: it searches footage by what happens in it and returns the timecode with enough context around it to judge whether that is the take you meant. It reads the storage a team already uses, so the folder structure everyone complains about does not have to be fixed first.
The routes, and what each one costs
A shared drive with a naming convention is free and works better than people admit, up to the point where the person who invented the convention leaves. Then the convention becomes archaeology.
A general DAM with AI features bolted on is strong on rights, approvals and brand assets. Video is often a second-class citizen inside it, so check playback, proxies and how it handles a two-hour file before you assume parity with images.
A video-first system is heavier and made for footage. It expects an owner, someone whose actual job includes ingest discipline. Without that person it decays quietly.
A retrieval layer over existing storage is narrower by design. It answers where something is and does not touch approvals, rights or versioning, so it either sits next to your system of record or leaves those problems unsolved.
Asking the person who shot it is genuinely the fastest option on a small team. It stops working the week that person is on another job, and it degrades every time someone leaves.
When a creative team does not need one
If your output is made once and rarely reused, a catalog is overhead. If the whole library is a few hundred files, two people can hold it in their heads more accurately than any tagging model. And if the team will not maintain metadata today, they will not maintain it after purchase either. A system nobody fills is worse than a drive, because it makes people think the search was already tried.
There is also the case where retrieval is not the bottleneck at all. On a lot of small productions the slow part is selection judgment, working out which of nine usable takes is the right one, and that is taste, not search.
Four questions worth asking
Who maintains the vocabulary the AI produces, and what happens when it tags things with words your team does not use.
What happens to material that arrives while nobody is watching, on a weekend or during a shoot.
Can somebody outside the media team find a clip without asking the media team.
Can you get your metadata out, in a form another system can read, on the day you leave.
If the thing hurting your team is approvals, rights and where final files live, buy the system of record and accept that its search will be ordinary. If the pain is that the material is all there and nobody can put their hands on the right forty seconds of it, search behaviour is the product and the rest is packaging. Most teams have both problems and can only afford to solve one properly this year. Solve the one that stops work today.