Learn how CloudFactory’s managed workforce worked with 3 companies, each with a problem involving data, automation, and/or ML.
CloudFactory Blog
From data collection to training and deploying working models, the development of medical AI comes with many important challenges and opportunities.
From faster drug discovery to robotic surgery, AI is transforming the healthcare sector with promises of improved patient care and reduced costs.
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.
An incremental design approach to automation and machine learning affords strategic opportunities for choosing to route exceptions to machines or people.
Optical character recognition (OCR) can improve productivity when transcribing text, but people still play a critical role in quality control.
Choosing a managed workforce to take care of your data entry needs can help overcome the challenges of scale, quality control, and communication.
Accurate data entry is the foundation of strong financial practices. It helps finance teams maintain complete records and expedite critical transactions.
Automation and AI hold great potential to innovate, improve, and make predictions. Here are three mistakes you’ll want to avoid.
Data entry is an essential part of the digital transformation process for legal firms seeking to speed discovery and provide better client experiences.
Data entry is a crucial part of any digital transformation project. Sometimes it makes more sense to outsource than to burden your own team.
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.
CloudFactory’s project managers lead teams that deliver client work. Meet one of our leaders in Nairobi, Kenya, and read about a typical day for her.
After schools closed due to COVID19, CloudFactory USA partnered with Durham organizations to accelerate digital equity among school-age children.
How can you determine if a data labeling service will deliver quality work? How they communicate and handle quality control are key indicators.
