Six months later the same buyer is drowning in filtering costs, burning engineering hours on data curation, and still missing the edge cases that matter most.

The sticker price was low. The total cost of usable output was brutal.

This keeps happening because procurement frameworks haven't caught up to the product. They're still buying synthetic data like stock photography. By the unit. By the pound.

But training data isn't stock photography. An image that doesn't match your sensor is worthless. An image that can't be controlled precisely is a liability. An image of a common scenario you already have a thousand of is noise.

The metric that matters is cost per asset that goes straight into your pipeline without rework. Ask any provider for that number. Most can't answer.

That silence tells you everything.