Our mission at Masterful AI is to bring the power and efficiency of modern software development to machine learning. One of the most archaic and error-prone aspects of ML development is getting accurately labeled training data. Through our work with many other ML engineers, we've seen a common fear: no one really knows if simply throwing more labeled training data at their model is going to deliver the accuracy they need. This has big implications, since labeling is slow and expensive. In this post, we'll share a framework and online calculator you can use to evaluate the ROI of spending more money on labeling.