Data Labeling services for Artificial Intelligence
WeSage experienced annotators can classify images, text, audio, video, social media posts, and comments. We are fully equipped to handle millions of annotations per month and our dedicated team of specialists is ready to assist your Machine Learning (ML) programs for large-scale projects.
WeSage BPM provides high-quality image data, accurately tagged by our expert annotators.
Data labeling takes 50-80% of the time of the entire AI development process. We specialize in creating, labeling, tagging, and validating the data from various forms like image, voice notes, or texts, among many other forms of data, and deliver it ready for the Model to interpret the data. Only after the data labeling process is completed, the models can learn and evolve.
Most of the time, the AI technologies need to be updated with the correct/updated version of data. This is why data labeling is a critical or integral part of the technology evolution process. Here’s when we help AI companies with our expertise in data capturing/labeling, data tagging, and data validation. We deliver the data ready for the model to be trained.
Please feel free to go through our case study wherein we helped one of our clients bring down the error rate from JUST 0.04 from 0.16 through our data labeling service.
Why Data Labeling is Important?
In today’s age, we see everything being automated with AI. How are automated systems built? Through programming? Yes, however, most of the systems cannot be automated just by developing a code. In order to develop a software with AI, a lot of data processing needs to be done. The data processing can be manual but is usually performed or assisted by software. A few studies have shown that Data labeling takes 50-80% of time of the entire AI development process.
Most of the ML and deep learning systems need huge amount of data to build the basis for a predictive and accurate learning system. The data used to train a model must be labeled or annotated based on data features.
The labels used to identify data features must be informative, discriminating and independent to produce a quality algorithm. A properly labeled dataset provides a basis for the MLL model which that data uses to check its predictions for accuracy and to continue refining its algorithm.
Different types of Data Annotation to meet your specific needs.
We have trained data annotators who will carry out the best out put from various types of subjects. We will prepare data according to the most vital variables and visual feature to apply the best labeling types.