Text Data Labeling, Editing, and Review for an AI Technology Company

Have you ever used a customer service chatbot like Siri or Alexa? What about Google Translate? All of these AI technologies are fueled by natural language processing (NLP).

NLP technology teaches machine learning algorithms to understand and generate appropriate responses to actual user queries – all thanks to immense volumes of meticulously labeled text data. In this detailed case study, TaskUs helps advance NLP research by working with one of the largest AI companies in the world.

The Challenge

Our Client, a leading AI technology company, wanted to teach their NLP model how to safely complete texts from unsafe or suggestive prompts. They needed a partner that could provide world-class text labeling, annotation, and editing support. This is where we come in.

The Answer Is Us

TaskUs’ teammates worked tirelessly together in thoroughly editing and reviewing 14 categories with almost 40,000 items that needed to be labeled and edited throughout the project using Labelbox: TaskUs’ data labeling partner, to review content generated by the Client’s AI model.

Our people-first, deep-dive approach to data labeling enabled our team to surpass the set metrics on skip percentage, categorization accuracy, and completion rate — achieving a score of 100% for each one. TaskUs prioritizes employees’ well-being, and since the teammates that worked on this project mostly dealt with harmful content, we incorporated wellness and mental breaks into the workday.

Learn more about TaskUs’ data labeling capabilities by downloading our case study, Text Data Labeling, Editing, and Review for an AI Technology Company.