NLP is one of the most difficult AI applications to develop and maintain. When you outsource data labeling, make sure you choose the right team.
Choosing a managed workforce to take care of your data entry needs can help overcome the challenges of scale, quality control, and communication.
Data entry is an essential part of the digital transformation process for legal firms seeking to speed discovery and provide better client experiences.
How can you determine if a data labeling service will deliver quality work? How they communicate and handle quality control are key indicators.
We are proud to announce that CloudFactory has been awarded the ISO 9001:2015 standard in Quality Management System.
How can you determine if a data labeling service will deliver quality work? It starts with their vetting, hiring, and training processes.
Humans play a critical role throughout the AI lifecycle, from data cleaning and labeling to quality control and automation monitoring.
Developing ML models requires a lot of data and skilled people to work with it. Here’s our HITL approach for machine learning model development.
When you have massive data to label for machine learning, it makes sense to outsource it. But what happens when your data is sensitive, protected, or private? Here’s a quick ...
Realizing AI’s potential benefits - and mitigating its challenges - will require collaboration. As partnerships form and critical questions arise across the globe in government, ...
Given the challenges of hiring and managing a team to complete the arduous data work behind AI, many companies are turning to outside help.
AI innovators rely on external teams to structure data for ML algorithms. But scaling quality data requires the right people & processes in your tech stack.