When In-House Data Annotation Stops Making Sense
And how to know you’ve reached that point In-house data annotation is a smart move at the start of most AI projects. It gives you speed, control, and fast feedback loops—especially when your dataset is small and the labeling rules are still evolving. But there’s a point where in-house annotation stops being an advantage and […]
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