A lot of data is required to develop an AI. However, it is not only about the quantity, but the quality is also crucial for the performance of AI. In order to keep the quality and the security of the data with deadlines, in-house workforce based system has strength over the crowd workforce based system. However, in-house system has a critical downside. It is expensive.
In order to overcome the problem, data labelling workforce in Africa was established to reduce the cost of the labor. And we would like to introduce how we manage the workforce in Africa to meet the complicated requirements and fast approaching deadlines of our clients.