AI Factory Model Webinar Series Part II

How to Build Your Data Production Line

Webinar + Panel Discussion + Q&A

Building Your Data Production Line

Watch the webinar to hear from data science and AI workforce experts about how to build your AI production line for high-quality data processing at scale.

Hear from experts in workforce operations (CloudFactory) and annotation tooling (Labelbox) to learn:

  • The 3 critical elements to include in your data production line
  • How to design your production line to meet quality and turnaround requirements
  • Why a managed workforce enables you to off-load your QA operation and contribute to higher quality data

WATCH THE WEBINARTell us about yourself

Guy Maskall

Guy Maskall Panelist

Guy is Lead Data Scientist at CloudFactory, and data science mentor and AI/ML advisor at Springboard where he helps shape their curriculums.

Philip Tester

Philip Tester Moderator

Philip is Director of Business Development at CloudFactory, where he creates partnerships to help solve data-production problems for AI innovators.

Brad Sheneman

Brad Sheneman Panelist

Brad leads the Applied Machine Learning team at Arturo, where he oversees the research and rapid development of new deep learning-based statistical models.

Brian Rieger

Brian Rieger Presenter

Brian is Co-founder and COO at Labelbox where he focuses on solving the tooling and data management challenges facing AI teams today.

Matthew McMullen

Matthew McMullen Presenter

Matthew is Growth Strategist at CloudFactory, where he connects AI development and operations teams with solutions that accelerate and scale the data production process.


For over a decade, CloudFactory has powered quality data at scale. Its managed workforce processes pipelines of big data with high accuracy on virtually any platform, with the expertise and communication of a trained internal team. As a global leader in impact sourcing, CloudFactory creates economic and leadership opportunities for talented people in developing nations.


Labelbox is a new way to create and manage training data. Rather than requiring companies to create their own expensive and incomplete homegrown tools, Labelbox is a training data platform that acts as a central hub for humans to interface with AI. When humans have better ways to input and manage data, machines have better ways to learn.