When implementing growth strategies beyond their capabilities, business organizations tend to thinly distribute their resources, neglect the protection of their core business, or venture into areas that the company is unfamiliar with or has the potential for significant risk.
For AI data solution companies, their core business is to produce and develop AI models that support efficient business operations for their clients. Data Collection and Annotation is a prerequisite for building AI models, and it also accounts for the majority of the time and effort spent on AI/ML projects (up to 60-70% of the product outcome). When experts participate in cleaning and labeling data, they must allocate time to perform “tedious” and “redundant” tasks beyond their capabilities. As a result, the product development cycle will begin to experience delays due to overlapping processes, leading to inefficiency and customer dissatisfaction.
Moreover, the dispersion of efforts blurs the focus on core business value development, resulting in increased costs, decreased productivity, and customer satisfaction. Departments such as human resources and accounting have to take on additional tasks. The accounting department decreases its focus on higher-level tasks and its core business functions. The human resources department does not have much time to focus on employee benefits and company culture.
Outsourcing the preprocessing process can help you rationalize the entire system and ensure that the development process takes place simultaneously. Your employees can focus on long-term goals that are truly important to the company. In addition, your AI/ML development team can focus on their core competencies and value by building solutions based on high-quality processed AI datasets.
If you are looking for a third party that can help you handle this work, please contact Beework. We can turn your worries into the peace of mind so that you can focus on your core business of building AI models.
