Build vs Buy: The Real Cost of Running Your Own Computer Vision Pipeline

Every team that considers building its own computer vision pipeline starts with the same napkin math: a few GPU instances, some open-source models, maybe a couple weeks of engineering time. It looks cheap. It almost never is. The sticker price of "build" hides a second, larger invoice that shows up six months later in the form of on-call pages, retraining jobs, and a roadmap that quietly stalled because your best engineer is debugging inference latency instead of shipping the product.

This post is not a pitch dressed up as analysis. Building your own pipeline is the right call for some teams, and we will say exactly when. But for most teams shipping a product where computer vision is a feature rather than the whole business, the real cost of building rarely gets accounted for honestly. Let's break it down.

The Visible Costs: What Shows Up on the Invoice

These are the costs that make it into a budget spreadsheet, and they are real, but they're also the smaller half of the story.