Five Reasons to Outsource Your Data Annotation Project

Artificial Intelligence (AI) and Machine Learning (ML) development is mainly rely on training data sets, that helps the AI or ML algorithms to detect the objects and learn certain patterns for future predictions. And acquiring the labeled or annotated data is the real challenge for the companies they many times prefer to generate such data from in-house sources.

Actually, such companies believe that using the internal sources will not help them to save time and cost, but their data will be remain confidential within their employees. And security is also another concern in-house annotation gets better reliability. But right here we discuss why data annotation outsourcing is the better option for AI and ML companies.

#1 Get Better Quality Training Data Sets

Quality and accuracy is the prime factors plays a key role in success of the AI or machine learning model development. And the quality or accuracy comes with the expertize and experience, which is possible with the professionals dedicatedly into performing such tasks.

Here, if you outsource data annotation to industry experts, you will assign your requirements to professionals who are highly skilled and work with much faster pace with better quality. They work in a team and know all the aspects while annotating the images making sure the quality should be at the best level while generating high volume data.

Also Read:  How To Ensure Quality of Training Data for Your AI or Machine Learning Projects?

Anolytics is one of the hidden gems, that provides data annotation services for machine learning and AI projects with the best quality and accuracy. It has a well-trained team to complete such projects timely that goes through multiple quality checks for zero error. It ensures the quality of every data annotation project while maintaining cost and productivity.

#2 Timely Availability with Live Annotations

If you try to acquire such data from internal sources, your project might delay due to the slow delivery of projects from in-house employees who are already busy completing the annotation of hundreds of images or on-going projects.

Here, if your project needs urgent annotated data to complete the model timely, you need to find the experts providing the live annotation services. Outsourcing will be the better option, that will help you get quality datasets at a faster speed.

Analytics, works with speedy annotation services to label the images for machine learning with an edge. It has delivered data annotation projects for different fields and gained the expertise to complete such tasks at a faster speed with accuracy.

#3 Scalable Solution with Turnaround Time

Training the machines requires a huge quantity of labeled datasets to make sure the model gets the feed of most of the variety learned from the data and gives precise results. And if the project is based on deep learning you need big data to train the model to understand the complexities of the algorithms and produce acceptable results.

In such conditions how will you meet your annotated data demand from your in-house team, and if you hire more team members for a particular project it will add cost to your final project development and maybe they also unable to meet your demand.

Anolytics works with a scalable solutions to provide large volume training data solutions to AI and ML companies. Data annotation outsourcing to such professionals also helps you to get the annotated data rapidly with a turnaround time to meet your uncertain demand that can come anytime, into any language or from any unexpected fields.

#4 The Security and Confidentially of Data

The security of data is another factor AI or ML companies think about seriously while outsourcing data annotation services. Few companies avoid outsourcing such projects due to data privacy compliance like PII or PHI or other considerations. But it’s not true, as professional companies work with ethics and never misuse the data of their clients or share it with others without permission from the clients.

While on the other hand, using internal sources to annotate the data can be useful for small companies working on simple AI or ML projects. But for bigger projects and deep learning you need to outsource the annotation projects to a third-party to build the right model.

Anolytics works with legal stipulations while accepting the annotation projects to ensure the security of data till the end of delivery of projects. It is working with a wide number of clients to make sure the unannotated and annotated both types of data are secured. It is also a SOC 2 TYPE 1 certified company and maintains high standards of data security and confidentiality.

#5 Outsourcing Rationalize the Internal Bias

Another one of the best advantages of outsourcing the training data to third-party companies is, that rationalizing the bias in machine learning generates results that are systematically partial due to inaccurate assumptions. And when such situations occurs the accuracy of data suffers affecting the productivity of ML model when used in real-life.

The most common causes of bias in machine learning training data are, when you use to train your model not accurately represent the environment that the model operates in real-life use. However, no data set can give you the real world with 100% accuracy.

Biased results from training data are also influenced by other factors like cultural or other stereotypes followed during the annotation process. And many times internal biased also finds the space in such projects that create a preconceived expectation of the model prediction that leads to an unconscious data annotation with the given result in the minds.

Summing-up

Hope these five reasons to make you understand why you need to outsource data annotation projects to other companies who are working with a professional environment. Anolytics works with dedicated team to annotate a huge quantity of data including texts, videos and images with the highest level of accuracy. It can meet your data, Image, audio and video annotation requirements with a scalable solution and complete security for a reliable annotation solution at low cost.