This is the best summary I could come up with:

Building your own is an option, but the expertise required to train and deploy modern CV models is non-trivial: unless you have the time and money to stand up a real team, it may be out of your reach.

That’s the type of situation that Viso wants to remedy, by providing a platform to create an enterprise-grade CV model of your own without dedicating the kind of time and resources that it often takes.

However, they eventually need to bring all computer vision initiatives together (streamlining), and deeply integrate and customize them, and also ‘own’ them because the data is sensitive and the technology of strategic value.

Computer vision requires data to start with, and training processes, and then implementation, hosting, compliance work, and so on — and it seems to really be a “soup to nuts” solution that puts all of that in one place:

That would include low-level analysis and storage of the raw data, annotation and labeling, training and testing of the base model, product integration, deployment online or offline, analytics, updates and backups, as well as access and security… all without leaving Viso, and probably without touching the semicolon or bracket keys.

Not being a developer myself, I can’t speak to how difficult or easy different use cases might be, but certainly there is a fundamental attraction (as evidenced by the popularity of other low-code and end-to-end tools) to using fewer and more comprehensive platforms rather than stitching together a series of disconnected ones.

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