Is it worth managing your data labeling in-house?
High quality data is the most important factor in building machine learning models. The majority of the time, training data presents problems stemming from how the data was produced and labeled internally. Other times, AI projects stall because of the lack of internal resources and skills to label data.
Achieve higher levels of model accuracy
Reduce costs by reallocating expensive resources
Save costs and complete projects faster