Raise a round right now and investors will ask about your model, your team, and your traction. The thing that quietly decides all three rarely makes the pitch deck: where your data comes from, and whether you can keep getting it cheaply as you grow.
Founders feel this before anyone else. A model is only as good as what it’s trained on, and the data worth training on is almost never sitting in one clean, downloadable place. Teams that figure out acquisition early ship better models and burn less runway doing it. Teams that don’t tend to lose a quarter to it and wonder where the money went.
The difference usually isn’t budget. It’s a handful of decisions made before the problem got expensive.
Start with what’s already public
The cheapest first move is to take inventory of what’s free. Common Crawl holds petabytes of web data, and Hugging Face hosts hundreds of thousands of open datasets you can pull today. For a pre-seed team, that’s often enough to get a prototype in front of someone who can fund the next step.
