Learn how CloudFactory’s managed workforce worked with 3 companies, each with a problem involving data, automation, and/or ML.
From data collection to training and deploying working models, the development of medical AI comes with many important challenges and opportunities.
An incremental design approach to automation and machine learning affords strategic opportunities for choosing to route exceptions to machines or people.
Could the secret to developing ML be more boring than we think? It’s time to give up the quest for the perfect model.
What will 2021 bring to the world of AI and machine learning? CloudFactory CEO and founder Mark Sears shares our predictions.
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.
We are excited to announce a new offering that bundles our professionally managed workforce with a market-leading annotation platform for one price.