Why to outsource Data Labeling Services

Data Collection and labeling are the core of any Machine learning model. These self-learning models require plenty of annotated information to train before they go live. So for many companies and researchers looking to develop AI or machine learning algorithms, there's a choice that they have to make:- Do they have to outsource or do in-house labeling.

There are different aspects they need to consider before making the right choice. Focusing on security issues, one may go with in-house labeling. But Quality and cost are the other sides of the coin. In reality, there are benefits and hidden pitfalls in both of these approaches. Choosing the right one is a strategic decision, which may affect the overall developing process.

In the beginning, your labeling project might involve lots of subjective judgment elements and complex scenes. At this point, it is better to keep the annotation in the house to keep it agile. As your labeling requirements become clearer and data volume increases, you should consider adding outsourced services to increase the capacity of your labeling operation.

Benefits of outsourcing

Outsourcing Data labeling services allow your company to work with experienced and specialized annotators

• The advantage of outsourcing your data annotation project is that professional annotators will deliver the highest level of data quality necessary to rapidly progress your project. In this way, you can focus on your project while we take care of your data.
• It’s reasonable to outsource your data annotation to a professional team that is well-equipped to tackle high volumes of data and have them deliver high-quality datasets faster without compromising on accuracy.
• Annotation companies are well aware that the security of data is essential and have data confidentiality agreements. At TagX we are particularly sensitive to our clients’ privacy concerns.

Therefore companies should carefully consider four aspects of data annotations before turning to internal resources for their data annotation needs. Concluding, outsourcing labeling needs is the ultimate time and resource saver.

Additionally, when doing business with the labeling partner, parties must establish an agreement that provides the specifics for labeling. Among the points required to include are subject-matter, the purpose of processing, the time frame during which the data may be processed, type, and categories of personal data, obligations, and rights.