Typically, in-house employees can manage your data needs with reasonably good quality—until it’s time to scale your model. Contractors and freelancers are other options, but you need to train and manage them and control quality. It’s not easy, and costs can balloon. When you crowdsource, you use the cloud to send data tasks to many people at once. The problem with crowdsourcing is that compensation is usually based on speed, so quality suffers, and attrition is high. CloudFactory’s managed workforce model combines the expertise and quality of a trained, in-house team with the scalability of the crowd so you can get to market quickly with the highest quality annotations. Because annotators must meet or exceed strict quality standards, you get the same (or better) quality than you would from internal teams—without the burden of team management. Our model is ideal for data work because dedicated teams understand your business rules. They stick with projects long-term, enabling them to increase their throughput and accuracy while consistently providing high labeling quality. We also support the entire AI lifecycle, giving you the flexibility to modify the scope of projects as your needs change. This flexibility will help you control costs as projects scale, something that’s prohibitively expensive when scaling with in-house teams or the crowdsourcing model.